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Location: New York, NY Workplace: Hybrid ABOUT THE COMPANY Rain is the global stablecoin payments platform for enterprises, neobanks, platforms, developers, and AI agents. Our technology allows partners to move, store, and use stablecoins instantly and compliantly through global payment cards, rewards, on/offramps, wallets, and cross-border rails. As both a Visa and Mastercard Principal Member, Rain issues cards that work at more than 175 million merchant locations in over 220 countries and territories. Built natively for stablecoins and trusted by more than 100 organizations worldwide, Rain delivers secure, scalable infrastructure that makes money move freely and instantly around the world. You will have the opportunity to deliver massive impact at a hypergrowth company backed by some of the top investors in fintech, crypto, and SaaS. In January 2026, we closed a $250M Series C led by ICONIQ, valuing Rain at $1.95B, with Sapphire Ventures, Dragonfly, Bessemer Venture Partners, Galaxy Ventures, FirstMark, Lightspeed, Norwest, and Endeavor Catalyst also participating. If you're curious, bold, and excited to help shape a borderless financial future, we'd love to talk. OUR ETHOS We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company. About the Role AI agents are already booking travel, subscribing to software, running procurement end to end, and moving money on behalf of users — much of it through Rain. Our Agent Control Layer is the governing surface for that activity: it enforces approved counterparties, amounts, merchants, and task scope at initiation, before a transaction ever occurs, rather than reconciling damage after the fact. We are hiring a Senior Product Manager to own that platform. This is a 0-to-1 role inside a category being defined in real time. You will own the developer-facing surface — APIs, SDKs, controls, docs — that teams building agents use to give them spending power safely. McKinsey projects $3–$5 trillion in global agentic commerce by 2030. The primitives that make it trustworthy have not been built yet. You will build them. You will report to the Head of Product and work daily with engineering, risk and compliance, network partnerships, and the developers shipping on us. What you'll do • Define the primitives for agent authority: spend scopes, merchant and counterparty allowlists, velocity and amount ceilings, task-bound credentials, human-in-the-loop approvals, and clean revocation. • Own scoped virtual cards for agents — cards provisioned for a single merchant, amount, and task, retired the moment the task completes. • Extend the rest of Rain's stack (wallets, virtual accounts, onramps, offramps, cross-border payments) to agent initiators within the parameters our customers define. • Treat the API as the product. Own endpoint design, error semantics, idempotency, webhooks, sandbox and simulation tooling, SDKs, and reference agents. • Own documentation and the onboarding path with the same rigor as the product itself. Time-to-first-authorized-agent-transaction is your metric. • Run a tight design-partner loop with agent builders — read their integration code, sit in their debugging sessions, ship against what you find. • Build the roadmap from first principles: form a thesis on where agentic commerce goes next, sequence bets accordingly, and kill what isn't working quickly. • Partner with risk and compliance on Know Your Agent — agent identity, attestation, delegated authority, auditability, and dispute handling in a world where the cardholder wasn't the one who clicked. • Represent Rain's technical point of view in Agentic Payments Alliance working groups and with Visa, Mastercard, and stablecoin partners as standards take shape. • Write the specs, launch posts, and positioning that teach the market what controlled agentic payments actually means. You’ll likely succeed if you have • 8+ years in product management, with meaningful time on a developer-facing platform, API, or infrastructure product. You have shipped something engineers chose to build on. • Technical depth. You read API diffs, write your own queries, prototype against your own endpoints, and hold your own in an architecture review. You don't need to have been an engineer; you do need engineers to take you seriously. • 0-to-1 instincts. You have taken a product from a blank page to real usage in an ambiguous market, and you're comfortable with a roadmap that changes because the ground moved. • Payments or fintech fluency, or the obvious appetite to acquire it fast. Authorization flows, issuing, interchange, chargebacks, settlement, KYC/KYB - you know these, or you'll learn them in weeks rather than quarters. • Judgment under risk. Every control you design trades capability against loss. You can reason about that tradeoff explicitly and defend where you landed. • Strong writing. At Rain, specs, docs, and launch narratives are the job, not overhead. • Bias for motion. You would rather ship a narrow thing this month and learn from it than scope a broad thing for two quarters. Bonus attributes • Hands-on experience building or deploying AI agents - tool use, orchestration frameworks, MCP, evals. • Stablecoin or onchain payments background: settlement, custody, treasury operations, or wallet infrastructure. • Experience working directly with card networks, issuing processors, or sponsor banks. • Time at an early-stage company during a period of fast scaling. THINGS THAT ENABLE A FULFILLING, HEALTHY AND HAPPY EXPERIENCE AT RAIN: Unlimited time off 🌴 Unlimited vacation can be daunting, so we require Rainmakers to take 10 days minimum for themselves. Flexible working ☕ We support a flexible workplace – work from home, come into an office, or both. We want everyone to work in an environment where they're their most confident and productive selves. New Rainmakers receive a stipend to set up a comfortable home workspace. Easy to access benefits 🧠 For US Rainmakers, we cover 95% of your health, dental, and vision plan costs and 90% for your dependents, plus a 100% company-subsidized life insurance plan. Retirement goals💡 Plan for the future with confidence. We offer a 401(k) with a 4% company match. Equity plan 📦 Every Rainmaker gets an equity option plan so we all benefit from our success. Health and Wellness 📚 High performance begins from within. Rainmakers receive a monthly stipend to be used for eligible health and wellness spending like gym memberships/fitness classes, massages, acupuncture - whatever recharges you! In-office meals 🍜 Rainmakers working from the office enjoy lunch and dinner on us, covered with a DoorDash credit. Team summits ✨ Summits play an important role at Rain. Time together helps us build relationships and a common destiny. Expect team and company offsites, both domestic and international.

Location: Office, EU We are the creators of a new fintech era! Our mission is to revolutionize the world by making blockchain technology accessible to everyone in everyday life. WhiteBIT is a global team of more than 1,500 professionals united by a shared vision of shaping the future. We are building our own blockchain ecosystem to ensure maximum transparency and security for over 8 million users worldwide. Our cutting-edge solutions, rapid adaptation to market challenges, and technological excellence set us apart from traditional companies. Our official partners include Juventus, FC Barcelona, Lifecell, FACEIT, and VISA. Join us as a Head of Data Platform. Requirements : Education & Experience: — MSc in computer science, mathematics, statistics, physics or another quantitative field; PhD is a plus, not a requirement — research-grade methodology sits with the Quantitative Researcher — 5+ years in data engineering / analytics, incl. lead / management experience; built a trading / financial data platform from zero at a crypto exchange, HFT / electronic-trading firm, market maker, or trading fintech. Bank / enterprise-DWH background alone does not qualify — Personally carried production ownership of money data — trades, balances, positions, P&L — where a data error is a financial error Core Technical Skills — data platform: — Hands-on today: designs and ships pipelines personally — advanced SQL and Python; ClickHouse (or kdb+ / comparable columnar OLAP) in production — Streaming and batch in one architecture: Kafka or equivalent, event feeds with second-grade freshness alongside hourly aggregates; trading-day logic — metrics counted within a trading day that starts and ends at a fixed morning hour, with an automatic daily reset — Optimizes data footprint and computational overhead across every stage: selects the tech stack, partitioning logic, and execution flow based on cost-to-performance impact — Data-correctness engineering: reconciliation, idempotent backfills, late / duplicate event handling, data-quality monitoring and lag alerting — Vendor and API integration: institutional market-data providers (Kaiko / Amberdata class), exchange APIs, FX feeds; schema design and documentation others can build on Core Technical Skills — analytics & applied math: — Applied statistics at a working level: distributions, hypothesis tests and confidence intervals, correlation vs causation, time-series and aggregation pitfalls (session boundaries, survivorship, outliers) — enough to catch a methodological error in an analyst's query or notebook, and to have designed or reviewed metric / experiment methodology in past roles — Metric and semantic design: one written definition per metric (P&L, uptime, spread, fill rate) enforced across every report; analytical data models (marts / star schemas) that make those definitions computable and cheap to query — BI stack governance: Tableau / Grafana — performance, access control, versioned metric definitions; reviews dashboards for correctness rather than building them all himself — ML literacy: understands when a model is — and is not — needed and can supervise applied work; research-grade modeling remains the Quantitative Researcher's mandate Market & Domain Knowledge: — Trading data from practice, not textbooks: maker/taker, fees and rebates, perpetual funding, realized / unrealized P&L, inventory and exposure, order-book depth and spread, slippage, quoting uptime — Understands the consumers: how analysts, quants and desk heads use the data, and how market-quality / compliance metrics feed liquidity-provider terms — Has built and run a mixed organisation of data engineers and analysts: separate hiring bars and growth tracks, peer review of queries and dashboards as a standard, methodology documented before a number ships — Partners with quantitative research: turns the Researcher's methodology into production metrics and dashboards without distorting it; runs the sign-off process with quant and desk stakeholders — Treats balances and client data as confidential by default: access control, least privilege, audit trail, no raw-data leaks — Never ships silently wrong numbers: escalates early, cuts scope consciously, flags uncertainty in the data Mindset & Soft Skills: — Player-coach: the first months are personal hands-on delivery; scaling through the team runs in parallel, not instead — Speaks business: reports status in money and deadlines; prioritizes by P&L impact — which dataset unblocks which decision; no jargon walls with management and stakeholders — Owner of the direction's technical goals, not of a backlog: takes a business problem, decomposes it into tasks, executes and delegates Responsibilities — Platform: — Architect and ship the central data warehouse: every trade, position, balance and P&L across all trading services; an hourly contour for BI plus a real-time contour for monitoring; trading-day logic with automatic daily reset — Build the data layers behind LP terms: market quality (spread, depth near mid price, fill rate, per-order slippage), quoting-uptime start/stop events per maker and pair, external tier-1 benchmarks and FX feeds for regional fiat pairs — Close the data debt: gaps in realized-P&L coverage, history backfills, broken monitoring services — restore or replace — Set and hold agreed data-freshness targets and pipeline-health alerting; own schemas and documentation — Own analytics delivery end-to-end: the KPI rulebook published and signed, financial / attribution / historical-performance dashboards, compliance screens and provider scorecards — Enforce a single semantic layer: one definition per metric across every report; methodology documented before a dashboard ships — Quality gate: numbers are reviewed and challenged before they reach management; sign-offs from quant / desk collected per deliverable Responsibilities : — Hire leaders-first and onboard the technical team (~10 people: data engineering, analytics & BI, technical PM) per the approved hiring plan; hand tasks down without losing velocity — Single interface to exchange tech (requirements, acceptance, freshness targets) and to analytics / quant stakeholders; run delivery in Jira against the approved one-year roadmap — After the build: run the platform as a service to the direction — researcher-generated tasks, new metrics and pair groups, regular recalibration. Working terms Immerse yourself in Crypto & Web3: Master cutting-edge technologies and become an expert in the most innovative industry. Work with the Fintech of the Future: Develop your skills in digital finance and shape the global market. Take Your Professionalism to the Next Level: Gain unique experience and be part of global transformations. Drive Innovations: Influence the industry and contribute to groundbreaking solutions. Join a Strong Team: Collaborate with top experts worldwide and grow alongside the best. Work-Life Balance & Well-being: Modern equipment. Comfortable working conditions, and an inspiring environment to help you thrive. 22 business days of paid leave. Additional days off for national holidays.

Задачи: — Разрабатывать AI-агентов на Python — Интегрировать модели и внешние API — Работать с RAG и Tool Calling — Упаковывать решения в Docker — Разворачивать через Helm в Kubernetes — Работать с ArgoCD и анализировать логи — Исправлять ошибки и самостоятельно обновлять production-деплои — Работать с SCA-сканерами и зависимостями Требования: — 3–6 лет опыта, Middle / Senior — Python + LangChain / LlamaIndex / Semantic Kernel или аналоги — Docker, Kubernetes, Helm — Bash, debugging, анализ логов — Понимание AI Agents, RAG, Tool Calling — Глубокое понимание Python-зависимостей (pip, poetry, virtualenv) — Высокая самостоятельность: от кода до запуска в production Условия: — Формат работы: Remote — Занятость: Full-time — Зарплата: до 260 000 ₽ на руки — Оформление: ИП / СМЗ — Локация: РФ, гражданство РФ

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. We're looking for a Senior Computer Vision Engineer to join our Embodied AI team, focused on 3D scene understanding and semantics. A reconstructed environment is only useful to a robot once it knows what is in it: which surfaces are floor, which objects can be grasped, moved, or opened, where one room ends and another begins. You'll work hand in hand with our Research Scientists to take advances in open-vocabulary perception, 3D semantic labeling, and scene graph construction and turn them into reliable capabilities that embodied AI teams can use in production. This is an applied research role. You'll live at the boundary between a research prototype and a production pipeline: adapting methods so they hold up on messy customer captures, lifting 2D semantic signals into geometrically consistent 3D, defining what "semantically correct" means for a downstream policy, and feeding what you learn back into the research agenda. You understand that the difficult part is often not the core method, but the messy inputs, edge cases, operational constraints, and downstream requirements surrounding it. You care about quality, cost, latency, and reliability, and you know that a system is only successful when people can depend on it. This is a hands-on engineering role for someone who wants to build, ship, and own outcomes. You'll help shape both the technology and the product, while remaining close to the code and the problems our customers are trying to solve. What You'll Do - Productionize 3D Scene Understanding Capabilities - Turn research prototypes in open-vocabulary segmentation, 3D semantic and instance labeling, affordance prediction, and scene graph construction into reliable pipeline components and services that operate across varied customer data and environments. - Own End-to-End Output Quality - Ensure that reconstructed environments carry labels, instances, and relationships that are consistent, complete, and correct enough for downstream simulation and policy learning, and define what "correct enough" means for each customer workflow. - Bridge Research and Production - Work day to day with the Embodied AI Research Scientist: pressure-test new methods on real customer data, identify where they break, and bring production and customer constraints back into research planning to prioritize the advances that matter most. - Make Systems Robust to the Real World - Diagnose failures caused by capture quality, scene complexity, scale, calibration, coordinate conventions, and other assumptions that prototypes often leave implicit. - Build Evaluation and Quality Infrastructure - Create datasets, regression tests, quality gates, and benchmarking tools that help the team measure whether changes improve the system. - Improve Performance, Throughput, and Cost - Profile and optimize GPU and distributed workloads, reduce unnecessary reruns, and help establish the economics of running reconstruction at scale. - Work Across the Product Boundary - Partner with Embodied AI product and engineering teams to understand customer requirements and deliver capabilities that fit real training, evaluation, and deployment workflows. Help evolve the representations, tooling, and operational systems that allow reconstructed environments to move reliably into customer applications. What You'll Bring - 5+ years of computer vision experience and a bachelor's degree or equivalent, - Significant experience building and operating production computer-vision, machine-learning, graphics, or data-processing systems. - Deep hands-on experience with scene understanding: semantic, instance, or panoptic segmentation; open-vocabulary detection and segmentation; or vision-language models applied to perception. - Experience taking 2D perception into 3D, such as multi-view label fusion, 3D semantic segmentation, instance tracking across views, or scene graph construction over reconstructed geometry. - Experience delivering reliable computer-vision or 3D systems used by other teams or customers, including the evaluation that proved they worked.. - Practical command of 3D and spatial data, including geometry, camera models, coordinate frames, calibration, and metric scale. - Strong Python and PyTorch skills, with the ability to work in C++ or other performance-oriented environments when needed. - Experience with cloud infrastructure, GPU workloads, distributed processing, or large-scale data pipelines. Nice to Have - Hands-on experience with 3D reconstruction, photogrammetry, structure from motion, Gaussian splatting, neural rendering, or meshing. - Experience with SLAM, visual positioning, localization, or large-scale mapping systems. - Experience with robotics, simulation, or embodied AI applications, in particular how semantic labels are consumed by a policy or a simulator. - Built evaluation or benchmarking infrastructure for perception or reconstruction systems. - Experience optimizing large-scale GPU inference workloads for cost, throughput, or latency. - A publication record or contributions to widely used open-source perception codebases. - Advanced degree in computer vision, robotics, machine learning, or a related field. Competencies - Relentless bias for action. You make decisions and ship as if the company’s success depends on it, because it does. You set the pace, and drive the people around you to rise to it. - Intellectually honest. You know there’s just one job that underpins every other in a startup: find the truth. You are relentless in your pursuit of it, including when it challenges your own convictions, and you raise concerns when you see them — even when it's uncomfortable, and especially when it's unpopular. - Pragmatic. You have no patience for not-invented-here Syndrome and analysis paralysis. You find the fastest path to a working capability without one-way doors that undermine scaling. - Strong systems instincts. You understand that production quality includes reliability, observability, cost, latency, maintainability, and usability—not just algorithmic accuracy. - Comfort with ambiguity. You can make progress when the problem, data, and requirements are still evolving. Compensation & Benefits Base salary range of $229,500 to $255,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: London Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. Niantic Spatial's R&D Team in London is seeking a Research Scientist to push the frontiers of Spatial AI, advancing our Large Geospatial Model as a dedicated member of the Embodied AI group. You will invent and develop algorithms and systems that sit at the cross-section of computer vision, machine learning, AI, graphics, and robotics. We're passionate about discovery, so we're looking for scientists who want to learn, publish, teach, and deploy every new invention. What You'll Do - Develop New Spatial Representations - Develop new spatial representations that embodied AI can learn from, train in, and act on. - Advance Real-to-Sim Pipelines - Advance real-to-sim pipelines connecting real-world observations, 3D reconstruction, simulation, and robotic policy learning. - Solve Emerging Spatial Problems - Solve emerging problems that relate to spatial intelligence, 3D scene representation, training data, model efficiency, and interactive systems. - Take Capabilities Through to Evidence - Take new capabilities through to evidence: what changed for the policy, not only what changed in the reconstruction. - Build Prototypes - Build proof of concept prototypes, initially for internal use, where some will need to run at production scale on customer data. - Collaborate Across Research and Product - Collaborate closely with researchers, engineers, and product partners to bring novel models to production. - Publish Your Work - Publish and present your work. What You'll Bring - A PhD in computer vision, robotics, graphics, machine learning, or a related field, or equivalent research experience, with a publication record at top venues. - Substantial expertise in robotics or embodied AI, including experience in sim-to-real transfer, domain randomization, policy evaluation, and simulation-based learning. - Deep experience with 3D scene representations: Gaussian splatting, neural fields, meshes, point clouds, or implicit representations. - You have applied generative or diffusion models to 3D data, such as scene completion, inpainting, relighting, or novel view synthesis from sparse capture. - You have worked on 3D semantics, open-vocabulary scene understanding, or scene graphs. - Proficiency in Python and Deep Learning libraries such as PyTorch. - GPU or graphics programming experience, such as custom CUDA kernels, shaders, or differentiable rendering. - A track record of contributing to widely used open-source research codebases. Nice to Have - Proficiency in C++. Compensation & Benefits Base salary range of £103,500 to £202,500. Compensation also includes an annual bonus, equity, and a comprehensive benefits package. Location & Work Model This role is based in our London office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: San Francisco, CA; New York, NY; Atlanta, GA; Toronto Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. ABOUT THE RETAIL TEAM - The Retail team on Agent Engineering supports some of the largest and most storied consumer brands in the world – including Gap, Wayfair, Sonos, and ADT. Together, we’re reinventing what commerce looks like in this new, AI-first era. Our customers rely on us to not only deliver novel experiences, but also host hundreds of millions of shopper and vendor interactions across web, app, phone, and in-store channels every year. - Our team supports our customers’ customers in the moments that matter – whether that's guiding a shopper to the right product during a limited drop or a Black Friday surge, locating a package that never arrived, or troubleshooting an appliance that stopped working. Always true to each brand’s voice, we create seamless experiences that resolve issues, drive revenue, increase lifetime value, and build lasting loyalty. - Our team supports our customers' customers in the moments that matter most, from product discovery and checkout to order tracking and troubleshooting. Always true to each brand’s voice, we create seamless experiences that resolve issues, drive revenue, increase lifetime value, and build lasting loyalty. - Every engineer on the Retail Team is a product-led thinker; every PM on Retail is also tinkering and developing tangible prototypes; and every strategist on Retail is capable of owning an agent end to end. As a part of this team, you'll set the standard on what it means to go beyond your role, and help build the groundwork for the retail industry in the future. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in Silicon Valley, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Abstracting complex commerce systems into packages: Modernize the sprawl of order management, fulfillment, returns, and warranty systems behind the large retailer ecosystem by creating scalable packages that optimize looking up and updating orders for customers – from Shopify storefronts to decades-old homegrown Order Management System (OMS) and claims platforms. - Shipping the full discovery-to-checkout lifecycle: Build personalized shopping flows that carry a shopper from a vague idea to a completed order. This includes everything from building a recommendation engine that combines transcript-aware planning, structured filters, and semantic and keyword search to payment and order placement. - Building production-grade agents at a truly global scale: Sierra’s retail agents serve some of the world’s largest global brands, handling traffic at unprecedented volumes during the busiest times of the year and across all geographic locales. You will be building at the frontier of enterprise applied AI. WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems. - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments. - A builder and tinkerer's mindset with high agency - you find creative ways to overcome obstacles and ship. - Comfort working directly with customers to understand their needs and solve real-world problems. - Excellent communication skills—clear, direct, and persuasive across technical and non-technical audiences. - Excitement in the retail space and a care for helping some of the world’s top brands continue to build brand loyalty with their customers. EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized  - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

Location: Metn, Lebanon About Toters Toters is an on-demand e-commerce and delivery platform and operates a service that enables customers to get anything in their city at the highest level of convenience. At Toters, technology is at the heart of everything we do. We have product teams that are working hard every day to create products that make our customers' lives easier. Our engineers are also continuously creating solutions to make our processes more efficient, all in an effort to get to our customers fast and at the best cost. If you are interested in working in a high growth startup environment, and look to be part of a team that will potentially change the way customers shop in the Middle East, apply now. The Role As a Senior Analytics Engineer, you will act as the crucial bridge between Data Engineering and Data Analytics. In a fast-paced, high-volume transactional environment like ours, clean, reliable, and scalable data is everything. You will bring software engineering best practices to our analytics workflows, taking ownership of our data warehouse architecture, building robust data models, and designing the ELT pipelines that empower our analysts, data scientists, and business leaders to make high-impact decisions. What You’ll Do Advanced Data Modeling: Design, build, and maintain highly scalable and modular data models using dbt (data build tool) within our cloud data warehouse (e.g., BigQuery, Snowflake, or Databricks), turning raw data into a reliable "single source of truth." Pipeline Optimization: Architect and optimize ELT pipelines to integrate complex, high-volume datasets across our 3-sided marketplace (app clickstreams, operational logistics, merchant catalogs, and financial transactions). Engineering Best Practices: Champion and enforce software engineering practices within the data team, including version control (Git), CI/CD pipelines, code reviews, and writing DRY (Don't Repeat Yourself) code. Data Quality & Governance: Implement rigorous automated testing, alerting, and anomaly detection to guarantee data integrity and build trust with downstream stakeholders. Self-Serve Enablement: Design intuitive semantic layers and heavily documented data marts that empower Product Analysts and Business operators to independently explore data without writing complex SQL. Performance & Cost Optimization: Audit and optimize legacy queries, streamline warehouse compute resources, and ensure BI tools (Tableau) run with minimal latency. Mentorship: Elevate the technical baseline of the entire Data Analytics team by teaching advanced SQL, dbt modeling techniques, and performance-tuning strategies. What We’re Looking For Experience: 4+ years of experience in Analytics Engineering, Data Engineering, or a highly technical Data Analytics role, ideally within a high-growth tech company, delivery platform, or multi-sided marketplace. SQL & dbt Mastery: Unmatched proficiency in writing complex, highly performant SQL. Extensive, hands-on experience building production-grade environments in dbt (including Jinja, macros, and incremental logic). Cloud Data Warehousing: Deep conceptual and practical understanding of modern columnar data warehouses (Snowflake, BigQuery, or Databricks) and architecture best practices. Software Engineering Mindset: Fluent in Git workflows, command-line interfaces, and setting up CI/CD workflows for data deployments. Programming Skills: Strong proficiency in Python for API integrations, custom transformations, or pipeline scripting. Business Acumen: Demonstrated ability to translate complex operational logic (e.g., courier dispatch algorithms, funnel attribution, financial reconciliation) into elegant data architecture. Nice to Have Hands-on experience with modern data orchestration tools (Apache Airflow, Dagster, or Prefect). Experience managing event-tracking pipelines (Snowplow, Segment, Amplitude). Previous experience managing the semantic layer in BI platforms like Tableau.

Location: Remote - EMEA; France; Netherlands; Spain; Germany Workplace: Remote Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations. Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data. As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI. We're hiring a Senior Support Engineer to help customers run Qdrant's vector search engine reliably in production. You'll work Kubernetes-heavy, cloud-native environments every day, investigate hard technical issues, and turn what you learn into tools and workflows that make the whole support function faster. This is a chance to help shape a growing support team at an early-stage AI infrastructure company. WHAT YOU'LL OWN - Provide direct technical support to customers running Qdrant, mostly asynchronous rather than face to face. - Troubleshoot production issues across Kubernetes, cloud infrastructure, networking, storage, and the database layer. - Lead incident investigations and turn recurring problems into documented diagnostics and repeatable fixes, using AI-assisted tooling to speed up triage where it helps. - Partner with engineering and platform teams to resolve customer issues and feed learnings back into the product. - Build and maintain internal tools that make support workflows faster and more observable. - Write and maintain clear documentation for both customers and the internal team. - Lead by example through strong technical work, initiative, and collaboration with stakeholders across the company. Who You Are - 5 or more years in a customer-facing support or infrastructure role, ideally supporting production Kubernetes environments. - Strong, hands-on Kubernetes skills. A Certified Kubernetes Administrator (CKA) credential is a plus. - Proficient in Python or a similar language for scripting and automation. - Experience with Kafka or similar distributed systems. - Comfortable working in AWS, GCP, or Azure. - Solid understanding of database internals and how they behave under production load. - A proactive, ownership-driven mindset. You dig into ambiguous problems without waiting to be asked. - Clear communicator who can translate between technical and non-technical audiences. Nice to Have - Familiarity with vector search or vector database technologies. - Terraform and infrastructure-as-code experience. Security background is a plus. - Experience with observability tools (for example, Prometheus or Grafana) and automating support workflows. WHY JOIN US - A remote-first, international team working on cutting-edge AI infrastructure. - A competitive salary with additional perks. - Flexible working hours and async-friendly culture. - High ownership and real impact. - Open-source, engineering-driven culture. - Choose your own laptop equipment. For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy. Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist. Come build with us! FOR INFORMATION ON HOW WE HANDLE YOUR PERSONAL DATA, PLEASE REFER TO OUR RECRUITMENT PRIVACY POLICY https://qdrant.tech/legal/recruitment-privacy-policy/ #LI-REMOTE

Location: Remote - United States Workplace: Remote Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations. Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data. As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI. We're looking for a Solutions Engineer to own the technical side of our enterprise deals, partnering with Account Executives as the technical authority rather than a supporting player. You'll lead the scoping, pricing, and deployment of semantic search, image and video search, and on-premise and edge deployment solutions for our most complex enterprise customers. This is a hands-on, customer-facing role for someone with real depth in solutions engineering who's ready to run high-stakes deals independently. What you will own: - Own Technical-to-Commercial Strategy: Translate complex architectural requirements (multi-AZ, sharding, replication) into accurate pricing models and contract terms, independently protecting deal value in high-stakes negotiations. - Drive Deal Execution End to End: Own the technical sales workflow across Support, Product, and Engineering to unblock POCs, resolving cross-functional bottlenecks without escalation. - Identify and Mitigate Deployment Risk: Proactively spot noisy neighbor issues, latency bottlenecks, and resource contention before they threaten renewals or expansions, and advise customers on architectural fixes. - Lead Architectural Reviews and Migration Assessments: Run discovery sessions solo, validate use cases, and design migration paths from legacy search engines like Elastic, Solr, and OpenSearch to Qdrant. - Design Resilient, Production-Grade Architecture: Spec high-availability search clusters that meet demanding customer SLAs and throughput requirements, including for the most technically complex accounts. - Own Client Trust at the Executive Level: Serve as the primary technical authority during evaluation, guiding customers to value quickly and acting as a long-term advisor beyond the initial sale. Who you are - 2-5 years of technical, customer-facing experience in Sales Engineering, Solutions Architecture, or Technical Consulting, with a track record of owning complex, high-value deals independently, including at least 2 years of direct, hands-on vector search experience (Qdrant, Pinecone, Weaviate, Zilliz/Milvus, or similar). Background in data science, computer engineering, or a previous DevOps/SRE role, with demonstrated depth rather than surface exposure is preferred. - Strong scripting ability in Python or Bash, used to build reusable tools and validate business value at scale, not just one-off scripts. - Fluency in calculating total cost of ownership (TCO) and estimating hardware requirements (RAM, CPU, disk) for distributed systems, including for multi-region or highly regulated deployments. - Deep expertise in Kubernetes and cloud platforms (AWS, GCP, or Azure), with a clear point of view on how infrastructure choices affect cost and performance at scale. - Excellent communication skills, comfortable running the room with engineers, VPs, and business stakeholders alike, and able to influence without authority across internal teams.   Preferred Qualifications - Exposure to enterprise procurement processes, infosec questionnaires, or MSA redlines.   WHY JOIN US - A remote-first, international team working on cutting-edge AI infrastructure. - A competitive salary with additional perks. - Flexible working hours and async-friendly culture. - High ownership and real impact. - Open-source, engineering-driven culture. - Choose your own laptop equipment. For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy. Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist. Come build with us! FOR INFORMATION ON HOW WE HANDLE YOUR PERSONAL DATA, PLEASE REFER TO OUR RECRUITMENT PRIVACY POLICY https://qdrant.tech/legal/recruitment-privacy-policy/ #LI-REMOTE

Location: London, United Kingdom - Deliveroo Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. From real-time logistics to resilient infrastructure and marketplace optimisation, we design, build and operate technology that powers Deliveroo’s growth at scale. We’re looking for a BI Engineer to join our London team. This role is based in our London office with a hybrid setup, typically 3 days in the office. Get to know our Engineering team — what drives us, how we work, and what you can expect. About the Team The Core BI team builds and operates the services, integrations and automation that power business intelligence across DoorDash, Deliveroo and Wolt. Our platforms help analysts, Analytics Engineers, Data Scientists, Software Engineers and business teams discover trusted data and make informed decisions at scale. We combine software engineering, platform ownership, and a strong user focus to make BI tooling reliable, secure, scalable and self-service. The team supports the current BI ecosystem while helping shape a more integrated experience across the DoorDash group. About the Role As a BI Engineer on the Core BI team, you will build and operate the models, systems and automation behind our BI platforms. This will include supporting our extensive user base on our current BI stack (primarily Looker and Sigma) while helping shape a single, more integrated BI platform across DoorDash, Deliveroo and Wolt. You will own problems from discovery through design, implementation, deployment, and operational support. You will work closely with Data Engineers, Analytics Engineers, Data Scientists, Software Engineers, Product Managers and business teams to turn recurring user needs into durable, self-service capabilities. If you're energized by solving technical problems with data and comfortable being deeply embedded across several domains, this role is for you! You’re excited about this opportunity because you will… Own and evolve the semantic layer behind our BI platforms: LookML and Canvas BI models, metric and dimension definitions, and the governance that keeps them trusted Build and operate the Looker and Sigma platforms themselves: instance and workspace configuration, permissions and user attributes, content lifecycle, and API-driven automation Lead the development of self-serve tooling that removes manual BI administration, using usage analytics to decide what to automate, build or retire next Support BI platform migrations and deprecations across DoorDash, Deliveroo and Wolt while protecting access, governance, data integrity and business continuity Take part in operational support, production debugging and incident response for the BI stack, and fix the root causes you find Champion engineering standards in BI, including version control, code review, CI and testing for models and platform code, so changes ship safely and repeatably We’re excited about you because… 3+ years of experience in business intelligence engineering, analytics engineering, data engineering, or a similar code-first data role Strong Python and SQL skills, and hands-on experience using AI tools (LLMs, agentic workflows, AI-assisted development) to accelerate your own engineering work Hands-on experience building in a BI platform such as Looker (LookML) or Sigma, modelling and configuring it, not only building dashboards in it Experience with semantic or metrics layers (LookML, dbt or similar): defining metrics and dimensions, and keeping those definitions consistent as they are reused Experience running what you build in production: version control, code review, CI, debugging live issues and taking part in operational support Excellent communication skills, and comfortable self-organising in a fast-paced, distributed environment with both technical and non-technical teams Nice to Have Experience with modern data warehousing platforms (e.g., Snowflake, Databricks, Redshift) and ability to optimize performance Experience automating BI administration through platform APIs, or identity and access through Okta, SCIM or role-based access controls Experience supporting a BI stack across multiple brands, tenants or regions, or leading a BI platform migration Why Join Us? At Deliveroo, you’ll do work that matters—solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. ➡️ Want a deeper look at how we build? Check out our Tech Blog . We aim to create a fair process that lets your skills shine—our interview typically includes 3-4 stages. Explore our Engineering Interview Guide here to help you feel confident at each stage. Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Semantics Innovations — технологическая IT-компания, которая специализируется на разработке, тестировании и внедрении программного обеспечения для цифровой экономики и финансового сектора. Формат работы: гибрид в Астане, Казахстан.

Location: United Kingdom, London Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Role Overview: We are seeking a Senior Director to lead our Enterprise Reporting and Analytics Engineering organization, a team of analytics engineers, report developers, visualization specialists, and people leaders. This organization focuses on the last mile of the enterprise data supply chain: the semantic models, curated data products, metric definitions, and consumption experiences that turn engineered data into decisions. This is not a traditional reporting leadership role; the classic notion of “reporting” in the form of a myriad of dashboards and filters is racing towards obsolescence. But the need for data and insights, and the need to deliver it in a way that is digestible and actionable, is timeless. Yes, governed dashboards and trusted reporting remain the foundation, and this leader must be excellent at that foundation. But the mandate is to move the organization decisively beyond static reporting toward a proactive, intelligent analytics capability: partnering with Data Science to productize and visualize their models, enabling generative AI and LLM-based access to our data, building exception-based systems that alert users when outcomes deviate from expectation in a statistically meaningful way, and designing agents that monitor data continuously and deliver insight without being asked. Analytics engineering shares much of its DNA with data engineering — modeling, transformation, testing, version control, CI/CD, performance and cost discipline — but is oriented toward business enablement rather than platform and pipeline. Success in this role therefore depends as much on partnership as on technical depth. This leader will work shoulder to shoulder with Data Engineering on the boundary between platform and consumption, with Product Management on roadmap and requirements, with Data Science on advanced analytic products, and with Analytics Operations on a disciplined intake and prioritization process that makes the best possible use of finite capacity. The ideal candidate has spent years building the traditional foundations — governance, metadata, lineage, dimensional modeling, engaging with enterprise BI platforms— and is now looking to apply that rigor to a fundamentally different generation of analytic products in new and innovative ways. What you'll be doing: Organizational Leadership Lead, coach, and develop an organization of approximately 30 people, including managing through frontline managers; own hiring, role clarity, career pathing, performance management, and succession planning. Define a multi-year vision and roadmap for enterprise reporting and analytics engineering, and translate it into quarterly outcomes the team and its partners can measure. Partner closely with Product Management to jointly shape the multi-year enterprise end-to-end data strategy. Own the organization's budget, vendor relationships, and contractor or offshore capacity. Establish and sustain an engineering culture within an analytics function: peer review, automated testing, documentation standards, source control, CI/CD, etc. Analytics Engineering and Data Architecture Drive maturity of the last-mile architecture in partnership with Data Engineering: curated marts, semantic layers, reusable data products, and certified datasets that serve reporting, ai enablement, data science, and downstream applications. Define and enforce dimensional modeling standards, transformation frameworks, and modular, tested, version-controlled analytics code. Own the enterprise metric layer so that key business measures carry a single, governed definition regardless of where they are consumed. Partner with Data Engineering to define clear contracts and handoffs between pipeline and platform work and last-mile modeling, including shared tooling, standards, and escalation paths. Manage query performance, warehouse consumption, and platform cost as first-class engineering concerns. Data Governance, Metadata, and Lineage Own cataloging, business glossary, data certification, and stewardship workflows, leveraging tools such as Atlan as the primary metadata platform. Maintain column-level lineage across the analytics estate to support impact analysis, change management, audit, and root-cause investigation. Leverage data access provisioning and entitlement models, including row- and column-level security, in partnership with Security, Privacy, and Compliance. Collaborate with Data Engineering to drive data quality monitoring, freshness and availability SLAs, observability, and incident response for analytic assets. Enterprise Reporting and Data Visualization Drive analytics engagement by leveraging enterprise visualization and provisioning platforms, including Domo and Tableau, in partnership with Data Engineering. Ensure best practices are followed in data architecture, governance, adoption, performance, and total cost management. Set visualization and information design standards that make reports readable, consistent, accessible, and decision-oriented. Rationalize the existing reporting portfolio: retire redundant and unused assets, consolidate overlapping content, drive down tech debt and drive consumption toward certified sources. Build a durable self-service capability through training, templates, community, office hours, and clear guardrails on what belongs in self-service versus centrally managed content. Advanced, Proactive, and AI-Enabled Analytics Partner with Data Science to productize their work: build the visualization, interaction, monitoring, and feedback loops that turn models and research into products the business actually uses. Partner with Product Management and Data Engineering to enable generative AI and LLM access to enterprise data. This includes preparing the semantic and metadata foundation that makes data legible to models, delivering conversational analytics, text-to-SQL, and retrieval-augmented experiences on governed sources, and establishing guardrails, evaluation, and accuracy monitoring so that answers can be trusted. Build exception-based analytics that detect when an outcome deviates from its expected value in a statistically significant way, using seasonality-aware baselines, forecast residuals, control limits, and anomaly detection rather than static thresholds. Route those exceptions to accountable owners with context, likely drivers, and a recommended next action; actively tune sensitivity and volume to prevent alert fatigue and preserve signal. Design and deploy analytic agents that proactively monitor data, investigate variances, assemble narrative explanations, and deliver insight into the tools where people already work. Shift the organization's consumption model from pull to push: the measure of success is not how many people opened a dashboard, but whether the right person was told the right thing at the right time. Cross-Functional Partnership, Intake, and Prioritization Operate as a true partner to Product Management: contribute to roadmap, requirements, user research, and release planning, and run analytics with a product mindset covering personas, adoption metrics, and asset lifecycle management. Partner with Analytics Operations to run a transparent intake, triage, sizing, and prioritization process, with published capacity, explicit tradeoffs, and reliable delivery commitments. Make capacity constraints visible to stakeholders and executives, drive reuse over one-off builds, and decline or defer work with evidence rather than friction. Serve as a senior, executive-facing partner to business functions, translating ambiguous business questions into well-scoped analytic solutions. What we're looking for: Bachelor's degree in Computer Science, Information Systems, Engineering, Statistics, Mathematics, Economics, or a related quantitative field; equivalent professional experience will be considered. 15+ years of progressive experience in data, analytics, or business intelligence, including 8+ years leading teams and 4+ years managing managers. Demonstrated experience leading an organization of 25 or more people in a large, matrixed enterprise. Strong hands-on foundation in SQL, dimensional modeling, and ELT/ETL design, with production experience on a modern cloud data warehouse or lakehouse (for example Snowflake, Databricks, BigQuery, Redshift, or Synapse) and a transformation framework such as dbt. Experience applying software engineering practices to analytics work, including Git-based workflows, automated testing, and CI/CD. Enterprise-scale leveraging of BI and data visualization platforms such as Domo, Tableau, Power BI, or Looker, including governance, provisioning, adoption, and cost management. Demonstrated ability to participate in driving data governance program covering catalog, lineage, glossary, stewardship, quality, and access, using platforms such as Atlan, Collibra, Alation, or Informatica. Proven track record of delivering jointly with Data Engineering and Product Management, with clear ownership boundaries and shared accountability. Direct experience partnering with Data Science, including operationalizing, visualizing, and monitoring model output for business consumption. Working command of the statistical concepts underlying exception detection, including hypothesis testing, confidence intervals, variance and control limits, seasonality, and forecasting. Experience running a formal intake, prioritization, and capacity planning process for a shared services or platform organization. Excellent executive communication and influence skills, with the ability to operate effectively amid ambiguity and competing priorities. Experience managing budget, vendor contracts, and platform licensing. Preferred Skills: Master's degree or MBA in a related field. Production experience delivering LLM-based analytics: retrieval-augmented generation over governed data, text-to-SQL or conversational BI, semantic layers designed for model consumption, and prompt, evaluation, and cost monitoring frameworks. Experience designing agentic workflows and orchestration for monitoring, investigation, and notification use cases. Hands-on experience with Atlan, Domo, and Tableau specifically. Proficiency in Python or R for prototyping, and familiarity with common statistical and ML libraries and MLOps concepts. Experience deploying anomaly detection at scale, including alert routing, suppression, and fatigue management. Familiarity with data product and data mesh operating models, domain-aligned ownership, and data contracts. Experience operating in an Agile or product operating model at scale, including portfolio, OKR, and roadmap management. Deep experience with the “Silicon Valley” school of Product Management, as exemplified by the “Marty Kagan”-style academic approach a significant plus. Experience leading global or matrixed teams, including offshore or vendor-partnered delivery models. Track record leading a major platform migration, consolidation, or reporting rationalization effort. Demonstrated success attracting, developing, and retaining senior technical talent in a competitive market. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

About LawnStarter LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. The company is expanding beyond lawn care to become a one-stop shop for all home services, operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform. About Analytics at LawnStarter The analytics team supports the entire company including product, marketing, operations, and finance. The data platform includes a centralized Redshift data warehouse, modeled in dbt and orchestrated by Airflow, with Segment feeding event data. The team is mid-migration to Lightdash as the single BI platform, replacing Tableau and Metabase. Currently, data quality, tracking standards, and platform hygiene are side tasks handled by analysts. The Role The Analytics Engineering Manager will be the first dedicated person for data governance, responsible for data trustworthiness and the roadmap to improve it quarterly. Responsibilities include ensuring quality and freshness of source data, pipelines, reports, metric definitions, Segment event tracking standards, Lightdash workspace health, data feeding ML models, and data security. The role involves collaborating with product, marketing, ops, and finance to prioritize platform work. It is a hands-on role starting solo, building automation, checks, fixing issues, and establishing scalable processes. Eventually, the manager will hire a Lead Analytics Engineer and grow the function as needed. Key differentiators of the role: - First dedicated governance role, reshaping existing standards. - Owns the data roadmap, discovering business needs and prioritizing work. - Whole-stack ownership from source data to ML models. - Leading the migration to Lightdash, setting up permissions and norms. Responsibilities: - Develop and manage the data roadmap balancing business needs and platform health. - Automate monitoring of data quality and freshness, resolve incidents. - Maintain data lineage and impact analysis to assess downstream effects of changes. - Administer Lightdash workspace, permissions, and rollout. - Extend and guard the semantic layer with governed metric definitions. - Govern Segment event tracking catalog, standards, and drift detection. - Ensure AI data readiness for internal AI tools querying the warehouse. - Manage data security, privacy, access controls, and compliance with US state laws. - Maintain governance documentation, ownership models, and review processes. Challenges to solve: - Convert business requests into a prioritized data roadmap. - Ensure Lightdash migration improves platform usability without dashboard sprawl. - Complete and maintain a trustworthy semantic layer. - Manage event-tracking standards and prevent entropy. - Proactively detect and prevent data pipeline breakages with automation and lineage. Success metrics for year 1: - Zero pipeline incidents from unannounced data changes. - Zero freshness incidents; stakeholders never see stale dashboards. - All business areas use official, well-maintained metrics and dashboards. - Every Segment event has an owner and meets standards. - Governance operates as a documented, sustainable system. Requirements: - Passion for data governance as a craft. - Daily use of AI tools for automation, anomaly triage, and documentation. - Hands-on manager who codes, debugs, and configures personally. - Product-minded, able to translate vague requests into prioritized plans. - Automation-first approach to quality checks. - Ability to enforce standards with clear rules and good tooling. Role exclusions: - Not a large-team leadership role; starts solo with potential to hire one lead. - Not a policy or committee role; hands-on fixing with code and conversations. - Not a BI analyst role; focuses on platform and guardrails, not dashboard building. - Not a mature system babysitting role; involves building and evolving the platform. Technologies involved: - Warehouse & pipelines: Redshift, dbt, Airflow - Ingestion: Fivetran, custom Airflow pipelines - Event tracking: Segment - BI tools: Lightdash (primary), Tableau and Metabase (sunsetting) - AI tooling: Claude Code, Codex, Brain (internal AI toolkit) - Observability: AI-powered Analytics Engineer agent for monitoring and anomaly detection Benefits: - Base salary $75k-$120k/year - Fully remote with asynchronous collaboration - Flexible PTO Equal employment opportunity statement included.

Location: London, United Kingdom - Deliveroo Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. From real-time logistics to resilient infrastructure and marketplace optimisation, we design, build and operate technology that powers Deliveroo’s growth at scale. We’re looking for a Software Engineer, Backend to join our London team. This role is based in our London office with a hybrid setup, typically 3 days in the office. Get to know our Engineering team — what drives us, how we work, and what you can expect. About the Team The Core BI team builds and operates the services, integrations and automation that power business intelligence across DoorDash, Deliveroo and Wolt. Our platforms help analysts, Analytics Engineers, Data Scientists, Software Engineers and business teams discover trusted data and make informed decisions at scale. We combine software engineering, platform ownership, and a strong user focus to make BI tooling reliable, secure, scalable and self-service. The team supports the current BI ecosystem while helping shape a more integrated experience across the DoorDash group. About the Role As a Software Engineer on the Core BI team, you will build and operate the backend services, APIs and infrastructure our BI platforms run on. This is a hands-on software and platform engineering role: services and integrations, identity and access automation, observability, reliability and developer experience. BI is the domain you serve (primarily Looker and Sigma, and the systems around them), but the problems are backend and platform problems. You will own problems from discovery through design, implementation, deployment, and operational support. You will work closely with Data Engineers, Analytics Engineers, Data Scientists, Software Engineers, Product Managers and business teams to turn recurring user needs into durable, self-service capabilities. If you're energized by solving technical problems with data and comfortable being deeply embedded across several domains, this role is for you! You’re excited about this opportunity because you will… Design, build, test, deploy and operate the backend services, APIs and automation that the BI platforms across DoorDash, Deliveroo and Wolt depend on Automate the platform lifecycle end to end (provisioning, metadata, permissions, migrations, archival and validation) so administration stops being manual work Build the integrations between BI platforms and the wider ecosystem: warehouses, identity providers, orchestration, CI/CD and internal developer tooling Improve the availability, observability, performance, scalability and security of the systems you own, and carry them in production Use AI tooling as part of how you engineer, and where it fits, build LLM-backed capabilities held to the same reliability and governance bar as anything else we ship Raise the engineering bar on the team, from service design and code review to testing, CI/CD and documentation, and improve the developer experience for everyone building on the platform We’re excited about you because… 3+ years of professional software engineering experience building and operating production backend, platform or infrastructure systems Readable, maintainable, well-tested code in Python, plus comfort with SQL and a working understanding of data modelling and warehousing concepts Experience building and owning APIs, integrations or automation in production, with sound judgement on service boundaries, authentication, data contracts and failure modes Hands-on with CI/CD, containers and Kubernetes, observability, debugging and incident response, and you expect to operate what you build Hands-on experience using AI tools (LLMs, agentic workflows, AI-assisted development) as part of how you engineer, and judgement about where they help and where they do not End-to-end ownership of ambiguous problems, clear communication with technical and non-technical teams, and comfort self-organising in a fast-paced, distributed environment Nice to Have Experience owning or integrating with BI platforms such as Looker, Sigma or comparable tools, and familiarity with semantic layers such as LookML or dbt Experience automating identity and access through Okta, SCIM or role-based access controls, or building multi-tenant platforms across brands and regions Experience shipping LLM-backed features to real users (retrieval, grounding and evaluation), or with MCP, agent frameworks or tool-calling in production Why Join Us? At Deliveroo, you’ll do work that matters—solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. ➡️ Want a deeper look at how we build? Check out our Tech Blog . We aim to create a fair process that lets your skills shine—our interview typically includes 3-4 stages. Explore our Engineering Interview Guide here to help you feel confident at each stage. Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Location: London, United Kingdom - Deliveroo Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Analytics organisation sits at the heart of Deliveroo powering decision-making across our 3 sided marketplace. We’re looking for an Analytics Engineering Manager to join our London team. This is a hybrid role, with 3 days per week on-site. In this role, you’ll lead a team of Analytics Engineers embedded in a key business domain, owning the pipelines, models and metrics that power day-to-day decisions and building the data foundations your stakeholders rely on. About the Analytics Engineering Org Analytics Engineering is a core pillar of Deliveroo’s Analytics organisation, alongside Data Science. With over 70 Analytics Engineers across the UK and India, we are embedded directly within product and business domains, owning the pipelines, models and metrics that power decision-making at scale: from self-serve AI-enabled analytics and experimentation through to executive reporting and strategic planning. The discipline is evolving fast. With new tooling changing how we work, we are shifting from building data pipelines to building AI first data products, developing rich semantic and data context layers and empowering self-serve data users. This role leads that work across a defined business domain, directly managing a team of Analytics Engineers and helping shape AE standards, culture and direction across the wider org. What You'll Be Doing Directly lead a team of Analytics Engineers embedded in a defined business domain, owning their performance, development and wellbeing Own the AE roadmap for your domain, identifying the highest-leverage investments, prioritising competing requests, and building the case for them with your business and product stakeholders Drive a data products mindset across your estate: clear ownership, SLAs, observability and data contracts built into how your team works by default Maintain strong technical involvement: reviewing data models and SQL, guiding architectural decisions, and stepping in hands-on when your team needs unblocking Contribute to AE-wide decisions on tooling, standards and process, helping shape how Analytics Engineering works at Deliveroo beyond your immediate team Build a high-performing, inclusive team culture by giving regular and actionable feedback, handling performance and motivation challenges, and running effective rituals Partner with Recruiting to hire strong, diverse AE talent into your team What You'll Need to Thrive Essential Experience in an Analytics Engineering, BI Engineering, or Data Engineering role, with strong, hands-on SQL foundations you still draw on regularly Proven experience managing a team of ICs, with a track record of developing people, giving hard feedback, and handling typical team situations independently Demonstrated ability to own a technical roadmap for a domain area and deliver against it with measurable business impact Strong grounding across the modern AE stack (cloud data warehousing, transformation tooling, data modelling, and data quality practices), with the ability to engage credibly on technical decisions and unblock your team Comfortable engaging and influencing at senior business and product level, with experience aligning analytics investment to domain priorities Nice to Have Experience in a marketplace, e-commerce, grocery or retail analytics context Familiarity with semantic and metrics layer tooling, or Python for data automation and pipeline work Exposure to AI for Data, including agentic AI methods, semantic layers, or AI-assisted analytics workflows Experience contributing to analytics ways of working: documentation standards, peer review processes, onboarding, and knowledge sharing Why Join Us? At Deliveroo, you’ll do work that matters, solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎A culture built for builders High standards, collaboration, flexible working and continuous learning. ​​ 💰 Share in the success you help create Competitive salary and equity options, so you’re rewarded for the impact you make. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Location: Germany; Portugal; France; Spain; Italy; The Netherlands Workplace: Hybrid WHY PRODUCT ENGINEERING AT LANGFUSE Your work will have an outsized impact. Everything you build is open source (MIT-licensed) and immediately visible. Langfuse has 35,000+ GitHub stars and our SDKs are downloaded more than a hundred million times per month. When you ship a new feature the community notices in GitHub issues, on X, and in our community channels. Product engineers at Langfuse are the people who deliver new features end-to-end to our users. You own the product thinking from understanding the user problem to deciding what to build to shipping the solution. You will also have direct exposure to how cutting-edge LLM applications are built. The users you serve are some of the best and most ambitious software engineers leveraging Langfuse to improve their applications. Deeply understanding the problems they solve will help you design the best possible product and along the way makes you an expert on LLM engineering yourself.   YOU WILL GROW AT LANGFUSE BY - Own features end-to-end: from talking to users, to writing the spec, to shipping the code and docs, to writing the changelog post https://langfuse.com/changelog with your name on it. To give you a sense: recent features a single engineer owned include the Langfuse for Agents https://langfuse.com/changelog/2025-11-05-langfuse-for-agents release (new trace views, agent graphs, semantic span labels), the TypeScript SDK v4 https://langfuse.com/changelog/2025-08-28-typescript-sdk-v4-ga rewrite on OpenTelemetry, and managing dashboards via API/CLI/MCP https://langfuse.com/changelog/2026-07-17-dashboard-and-widget-operations-in-api. - Work across the full stack: and we mean full. Our surface area is wide: React frontend, Next.js backend, ClickHouse analytics, Python and TypeScript SDKs, public docs, Terraform modules, and more. You'll touch whatever the feature needs. One week you might be writing a new ClickHouse query for cost analytics, the next you're designing an SDK API, the next you're building a new rust worker for faster data processing. - Talk to users constantly: jump on calls, respond in community channels, and route support requests. At Langfuse, support is how we build conviction about what to build next. Our handbook says it best: support by engineers is a core value proposition. - Write public documentation about the features you own. At Langfuse, docs are product. - Ship publicly during Launch Weeks: we've run four Launch Weeks https://langfuse.com/blog/2025-10-29-launch-week-4 so far, dropping a new feature every day for a week. Engineers present the features they built to the community.   WHAT WE’RE LOOKING FOR - Someone who has built features or even entire products from scratch end-to-end - Experience building and shipping user-facing products end-to-end, ideally in TypeScript/React and with exposure to data-intensive backends - Someone who can manage projects themselves. You know how to develop strong conviction about what to build and how to ship it. - Taste for great developer experience: you care about API design, UI details, and clear documentation - Interest in open source software and genuine excitement about talking to developers about their problems - Thrives in a small, accountable team where your output is visible and matters - CS or quantitative degree preferred Bonus points: - Experience with ClickHouse, analytics databases, or building complex data visualizations - Former founder or early startup experience - Contributions to popular open source projects - ML/AI background or familiarity with the LLM framework ecosystem No candidate checks all boxes. If you feel you are a good fit for this role, please go ahead and apply.   PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: SF or Remote (US/Canada) At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. APPLYING TO RENDER We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time. ABOUT THE ROLE We're looking for a Senior/Staff Data Scientist to join our growing Data team and serve as a strategic analytics partner across Render. As we scale, we're tackling increasingly complex questions across our product, customers, and business, from how developers discover and adopt Render, to what drives engagement and retention, to how we prioritize investments and identify new opportunities for growth. You'll partner with leaders and teams across Product, Growth, Go-to-Market, Finance, and other functions, focusing on some combination of data analytics, analytics engineering, machine learning, and experimentation based on your strengths, interests, and Render's highest-priority needs. You'll turn ambiguous questions into rigorous analysis, define how we measure success, and translate complex data into decisions and action. As a Senior/Staff-level individual contributor, you'll also help set the standard for analytics at Render, shaping our measurement frameworks, analytical practices, and how teams across the company use data to make better decisions. WHAT YOU’LL DO - Serve as a strategic analytics partner. Work closely with leaders and cross-functional partners across Product, Engineering, Growth, Go-to-Market, Finance, and other teams to identify high-impact questions, frame decisions, and determine how success should be measured. - Define meaningful metrics and measurement frameworks. Develop the KPIs and frameworks teams use to understand performance across areas such as acquisition, activation, adoption, engagement, retention, conversion, expansion, and customer outcomes. - Turn data into strategy. Surface patterns across our users, customers, products, and business. Identify opportunities, diagnose friction, and help teams determine where to invest and what to prioritize. - Shape our approach to experimentation and evaluation. Design and analyze experiments where appropriate, develop guardrail metrics and other methods for evaluating initiatives, and help teams choose the right analytical approach for the decision at hand. - Build measurement into how we work. Partner with teams to define instrumentation and measurement plans early, ensuring new products, programs, and initiatives can be evaluated reliably after launch. - Build trusted analytical foundations. Build and maintain dbt models, semantic and context layers in partnership with Analytics Engineering, transforming behavioral and business data into reliable datasets that support decision-making across Render. - Raise the bar for analytics. Establish analytical best practices, improve how teams use data in decision-making, and mentor scientists and cross-functional partners on measurement, experimentation, and data literacy. - Help shape the future of analytics at Render. Explore how AI-assisted tools can make analytics faster and more accessible while maintaining a high bar for accuracy, context, and analytical judgment. WHAT WE’RE LOOKING FOR - 7+ years of analytics experience, with a track record of shaping strategy and influencing decisions across complex or ambiguous problem spaces. - Strong business and product judgment. You can take an ambiguous question, identify what really needs to be understood, and determine the right analytical approach to inform a decision. - Experience defining and using metrics across some combination of Product, Growth, Go-to-Market, Finance, or other business domains, for example acquisition, activation, adoption, engagement, retention, conversion, expansion, or revenue. - Strong SQL skills. Writing complex, efficient SQL and independently exploring large datasets is a core part of how you work. - Experience using experimentation, statistical analysis, or other rigorous evaluation methods to understand impact, along with judgment about when each approach is appropriate. - Experience with modern analytics tooling such as Metabase, Mixpanel, dbt, BigQuery, Segment, and Git. - A track record of influencing cross-functional teams and senior leaders without direct authority. You're comfortable challenging assumptions, creating clarity from ambiguity, and driving alignment around what the data says. - Excellent communication skills. You can turn complex analysis into a clear narrative, explain technical concepts to non-technical audiences, and build the relationships necessary to drive action. - Experience using AI-assisted coding or analytics tools such as Codex, Cursor, or Claude Code to accelerate analysis, data modeling, instrumentation, or visualization. NICE-TO-HAVES - Expertise in statistical methods beyond traditional A/B testing, such as causal inference, cohort and survival analysis, or time-series analysis. - Experience with developer-focused, product-led, sales-led, or usage-based businesses. - Knowledge of cloud infrastructure, PaaS, developer tooling, or other technically complex products. - Experience analyzing multi-product or multi-segment businesses and understanding behavior across interconnected customer journeys. If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need. BENEFITS - 4 weeks of paid vacation. - 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return. - Long-term disability, life insurance, and 401K plans. - 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well. - Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc. - Monthly cell phone and internet subsidy. - Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders. - Continuous learning benefits & related support. This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization. Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. We encourage all who are interested to apply. We can't wait to hear from you! Render — CCPA Applicant Privacy Notice https://drive.google.com/file/d/1wKr9IejoT5McFrs9I2mahQnf6AFwb3z2/view Render — GDPR Applicant Privacy Notice https://drive.google.com/file/d/1_8jtyXQ1HdRdTdQn9sZ7n-R-zAGBmsFa/view

Location: SF or Remote (US/Canada) At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. APPLYING TO RENDER We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time. ABOUT THE ROLE We're looking for a Senior/Staff Analytics Engineer to join our growing Data team and lead the evolution of our Analytics Engineering platform. As Render scales, you'll build the foundations that turn raw data into trusted, reusable models for analytics, executive reporting, and AI-assisted decision-making. In this role, you'll partner closely with analysts, scientists, data engineers, and teams across Product, Engineering, Growth, Go-to-Market, Finance, and other business functions. Analysts and scientists will bring domain expertise and own business logic within their areas; you'll own the technical architecture, modeling standards, and engineering practices that help that work scale reliably. As a Senior/Staff-level individual contributor, you'll set the technical direction for Analytics Engineering at Render—strengthening data quality, improving the developer experience, and building semantic and context layers that make data easier to discover and use. You'll help teams move faster with consistent metrics and maintainable models they can trust. WHAT YOU'LL DO - Own our Analytics Engineering architecture. Guide the long-term evolution of Render’s Analytics Engineering platform, strengthening foundational models so our data remains trusted, scalable, and ready for AI-assisted analytics. - Build trusted, reusable data models. Design, build, and maintain governed dbt models that serve as authoritative sources for business-critical metrics across Product, Engineering, Growth, Go-to-Market, Finance, and other teams. - Establish engineering standards. Define and improve practices for data modeling, testing, documentation, version control, CI/CD, and code review. Review high-impact dbt changes and reduce technical debt across the analytics codebase. - Enable self-service and AI-assisted analytics. Design and maintain semantic and context layers that make metrics consistent, data discoverable, and analysis reliable for both people and AI tools. - Partner closely with analysts and scientists. Help analysts and scientists translate domain-specific business logic into scalable, maintainable warehouse models, moving shared logic out of individual reports and dashboards and into governed datasets. - Improve reliability and efficiency. Partner with Data Engineering to strengthen source data quality, warehouse architecture, and BigQuery performance and cost efficiency. - Raise the bar for Analytics Engineering. Mentor analysts, scientists, and analytics engineers on dbt development, dimensional modeling, and engineering best practices, and help teams adopt shared standards. WHAT WE'RE LOOKING FOR - 7+ years of experience in Analytics Engineering, Data Engineering, or a related technical field, including at least 3 years of hands-on experience running dbt in production. - Expert-level SQL skills and a track record of designing and owning scalable Kimball dimensional models. - Deep expertise in modern Analytics Engineering practices, including Git, testing, CI/CD, documentation, data contracts, lineage, and governance. - Experience building semantic and context layers, trusted metrics, and warehouse architectures that support self-service analytics for humans and AI agents across multiple business domains. - Strong understanding of modern cloud data warehouse architecture, performance optimization, and cost efficiency, with experience in platforms such as BigQuery, Databricks, or Snowflake. - A track record of establishing technical standards, influencing engineering practices without formal authority, and improving reliability while reducing technical debt. - Proven ability to partner closely with analysts, scientists, and business stakeholders to translate requirements into scalable, maintainable data models. - Excellent communication skills. You can explain complex technical concepts and tradeoffs to technical and non-technical audiences and build alignment across teams. - Experience building data models that connect product usage, acquisition, CRM, and financial data across the customer lifecycle. - Experience using AI-assisted coding or analytics tools such as Codex, Cursor, or Claude Code to accelerate data modeling, testing, documentation, or exploration. NICE-TO-HAVES - Hands-on experience with Render’s analytics stack, including BigQuery, Segment, dbt, and analytics tools such as Metabase or Mixpanel. - Experience with developer-focused, product-led, sales-led, or usage-based businesses. - Knowledge of cloud infrastructure, PaaS, developer tooling, or other technically complex products. If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need. BENEFITS - 4 weeks of paid vacation. - 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return. - Long-term disability, life insurance, and 401K plans. - 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well. - Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc. - Monthly cell phone and internet subsidy. - Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders. - Continuous learning benefits & related support. This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization. Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. We encourage all who are interested to apply. We can't wait to hear from you! 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