Вакансии

• 3+ years of Python development. • Production GenAI / LLM experience • Diffusion models & LoRA.

— проводить функциональное, регрессионное, smoke, UAT и негативное тестирование; — тестировать API через Postman / Insomnia;

Lead test strategy and quality standards across multiple projects, deciding what warrants automated coverage versus focused manual and exploratory testing. Build and maintain automated test suites in Playwright, and use BrowserStack to validate compatibility across browsers, devices, and platforms.

Build and support execution-engine components: Implement, test, debug, and maintain well-defined changes to query operators, expression evaluation, execution scheduling, and resource management.

The Cloud Engineer designs, secures, and supports mission-critical cloud infrastructure that enables reliable services for users worldwide. The successful candidate demonstrates strong technical judgment, operational discipline, and the ability to apply practical solutions to complex cloud engineering challenges.

Участие в разработке и развитии SIEM-системы KUMA: разработка контента и поставка экспертизы в решение; Работа с обращениями пользователей: проработка новых требований на основе фидбека заказчиков;

Задачи: — построение ETL-процессов: разработка и настройка конвейеров по сбору и трансформации данных из различных источников; — работа с современным стеком трансформации: освоение и применение DBT для превращения «сырых» данных в чистые аналитические витрины; — оркестрация данных: настройка и поддержка рабочих процессов (pipelines) в Dagster для своевременного и безошибочного обновления данных в отчетах; — управление хранилищами: работа с Postgres и высокопроизводительной колончатой базой данных Clickhouse для обеспечения скорости работы отчетов; — визуализация смыслов: разработка интерактивных BI-отчетов в Apache Superset для поддержки принятия бизнес-решений; — оптимизация выборок: анализ и ускорение тяжелых запросов для повышения производительности системы отчетности. Требования: — уверенное владение SQL (сложные выборки, агрегатные функции, оптимизация запросов); — понимание устройства реляционных баз данных, в частности PostgreSQL, и принципов построения аналитических хранилищ; — базовые знания Python, умение писать скрипты для обработки данных и автоматизации простых задач; — аналитический склад ума, способность работать с большими массивами данных, выявлять закономерности и структурировать информацию. Желательный опыт: — создание дашбордов в BI-инструментах (Apache Superset, Tableau, Power BI или аналогичных); — понимание концепций ETL/ELT; — понимание архитектуры данных, разницы между OLTP и OLAP системами (например, использование Clickhouse для аналитики); — интерес к современным инструментам DBT и оркестраторам данных (Airflow, Dagster). Условия: — срочный трудовой договор на 3 месяца; — график 5/2, не более 30 часов в неделю; — возможность работы удаленно, в офисе или в гибридном формате; — стажировка открыта для студентов любых ВУЗов и форм обучения, включая заочную и магистратуру.

— Разработка и поддержка AI-архитектуры: интеграция API (OpenAI, Anthropic), создание кастомных RAG-систем, оптимизация промптов и пайплайнов данных. — Быстрое UI/UX прототипирование: самостоятельное создание аккуратного, чистого фронтенда/интерфейса для разработанной вами AI-логики (работаем без лишних звеньев, напрямую в продукт).

• Resolve customer technical issues end-to-end (Helpdesk + Slack) within SLA. • Conduct root cause analysis with Grafana, Datadog (logs, metrics, traces).

Требования: — Наличие или получение степени бакалавра в области электротехники, компьютерной инженерии или смежной инженерной области.

‼️ Qo`shimcha: Biz jamoamizga full stack mobile engineer qidirmoqdamiz, backend + ios/android ilovalarni mustaqil yuritish, optimizatsiya qilish va rivojlantirish.

Требования: — Степень бакалавра в области электротехники, электронной технологии, электротехнической технологии, электротехники и компьютерной инженерии или в смежной области.

• Leverage AI to design and build features across backend, web, Android, and iOS. • Collaborate with product managers to shape goals into solutions and own the end-to-end development.

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're looking for an Engineering Manager to lead part of our Inference Performance team. This team makes the world's most demanding AI workloads run faster and more efficiently on GPUs. You'll manage and grow a team of inference performance engineers working across the inference engine and runtime: kernels, scheduling, batching, KV-cache management, speculative decoding and prefill/decode disaggregation. This is a hands-on technical leadership role. You'll set direction, unblock hard problems and earn the team's trust by going deep on GPU performance, while also hiring, developing and supporting the people doing the work. Your team's output directly affects how fast our customers' models run and how efficiently we serve them. The team is scaling quickly, so you'll help shape how it is structured as it grows. EXAMPLE INITIATIVES Your team will work on these types of projects as part of our Inference Runtime team: - Agentic inference optimization: 50-90% faster engines https://www.baseten.co/blog/agentic-inference-optimization-faster-than-sota/ - Agentic Kernels in Production https://www.baseten.co/blog/agentic-kernels-in-production/ - Live draft model training for speculative decoding https://www.baseten.co/blog/live-draft-model-training-for-speculative-decoding/ - The Baseten Inference Stack https://www.baseten.co/resources/guide/the-baseten-inference-stack/ RESPONSIBILITIES - Lead, mentor and grow a team of inference performance engineers through regular 1:1s, clear feedback, career development and performance reviews. - Hire top GPU and inference engineering talent, and build a strong, collaborative team culture as the runtime team scales. - Own the technical roadmap and execution for runtime performance work, balancing customer needs, new model launches and long-term platform investments. - Stay close to the technical work. Review designs, guide profiling and optimization efforts, and help the team reason from first principles about where time and memory go. - Drive the productionization of inference techniques such as quantization, speculative decoding, KV-cache reuse, chunked prefill and custom scheduling. - Turn performance wins into measurable outcomes: tokens per GPU-hour, utilization, latency and cost. - Help the team bring up and tune new model architectures on new hardware quickly, often in the same week they're released. - Partner with Infrastructure, Inference Platform, Kernels, Model APIs and customer-facing teams to set priorities, coordinate launches and ship wins. - Set high standards for engineering quality, benchmarking, operational excellence and incident response. REQUIREMENTS - Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or a related field. - Experience managing engineers, including hiring, mentoring, giving feedback and running performance reviews. - Experience leading or closely supporting GPU optimization teams in training, inference or recommendation systems. - Strong technical depth in GPU workloads, with a solid understanding of GPU architecture and performance tradeoffs. - Familiarity with ML libraries such as PyTorch, TensorRT or TensorRT-LLM. - A track record of driving roadmaps and shipping complex technical projects with a team. - Clear written and verbal communication, including the ability to align stakeholders across teams. NICE TO HAVE - Familiarity with inference engines such as vLLM, SGLang or TensorRT-LLM. - Experience with LLM optimization techniques (e.g., quantization, speculative decoding, continuous batching) in production. - Experience with GPU kernels (CUDA, Triton, CUTLASS, or similar). - Experience scaling a team through rapid growth at a startup. - A background as a hands-on performance or systems engineer before moving into management. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: United States Who We Are MEMX is a technology-driven exchange operator founded by members to benefit all investors. We operate MEMX Equities, MEMX Options, and MX2 Options, and provide market technology to clients. Our mission is to create healthy competition and advocate for market structure reform that results in more efficient and sensible trading experiences for all investors. Description MEMX is seeking a Network Engineering Intern to learn how the networks behind our U.S. equities and options exchanges are built and supported. You’ll work alongside experienced engineers on hands-on projects and gain exposure to the reliable, low-latency infrastructure that supports trading. This internship position will be offered as hybrid with 1- day in person at our Data Center in North Bergen, NJ, and 2-days in person at our co-working office in Midtown -NYC . Work Schedule The intern will be expected to work the following schedule: Monday: 1:00pm – 10:00pm ET, in person at our North Bergen Data Center Tuesday: 10:00am – 6:00pm ET, remote Wednesday: 9:00am – 5:00pm ET, in person at our co-working office in Midtown-NYC Thursday: 9:00am – 5:00pm ET, in person at our co-working office in Midtown-NYC Friday: 9:00am – 5:00pm ET, remote Hours are subject to change based on operational needs. *MEMX has currently approved ONLY the following states for remote work: California, Colorado, Connecticut, Delaware, Florida, Georgia, Illinois, Kansas, Maine, Maryland, Massachusetts, Michigan, Nevada, New Jersey, New York, North Carolina, Pennsylvania, South Carolina, Texas, & Utah. What You’ll Be Doing Help the team monitor network performance and investigate alerts and connectivity issues Assist with network device configuration, testing, and documentation under the guidance of experienced engineers Assist with data center activities such as racking, network and hardware, running optical fibers, etc. Contribute to projects involving network tools, automation, and infrastructure improvements Collaborate with teams across MEMX to understand how network engineering supports the exchange Requirements Current undergraduate student entering their junior or senior year, pursuing Computer Science, Information Technology, Network Engineering, or a related field Foundational understanding of networking concepts such as IP addressing, routing, and switching through coursework, projects, or personal interests Interest in troubleshooting and learning how large-scale networks operate Strong attention to detail and willingness to ask questions and learn from the team Exposure to Python, Linux, or Wireshark is a plus, but not required Ability to work in person at our Midtown Manhattan office during the summer Permanent residence in one of MEMX’s approved states for remote work during the internship What You’ll Gain Hands-on experience with the network infrastructure that supports a securities exchange Exposure to various Options and Equities exchange platforms and how network connectivity supplements these platforms Exposure to network monitoring, troubleshooting, and day-to-day operations Learn how customer connections are set up and supported Mentorship and guidance from experienced network engineers Opportunities to collaborate with technology teams across MEMX and connect with fellow interns Why MEMX At MEMX, you’ll contribute to meaningful work alongside experienced professionals while developing your skills and learning how our exchanges operate. As part of our summer internship program, you’ll also have access to: Learning opportunities: Attend Lunch & Learn sessions, professional development workshops, and relevant courses Mentorship and support: Learn from a mentor and a designated buddy who can help guide you throughout the summer An intern cohort: Connect with interns working across other MEMX teams Social events: Get to know colleagues, with opportunities to connect with members of MEMX’s C-suite Regular feedback: Check in with your manager and HR to discuss your progress, ask questions, and get support Future opportunities: All interns are considered for potential internship extensions or a full-time opportunity after graduation, based on performance and business needs Pay Rate: $30/hourly for undergraduate students Equal Opportunity Statement MEMX is an equal opportunity employer. We are committed to creating a diverse and inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Diversity Inclusion Statement At MEMX, we believe that diversity and inclusion are essential to driving innovation and success. We welcome and celebrate individuals from all backgrounds and perspectives, and we strive to create an inclusive culture where everyone can thrive.

• Проверять корректность финансовых расчётов: создавать эталонные сценарии, рассчитывать результат вручную и сверять его с движком. • Разрабатывать тесты-инварианты — проверять свойства, которые должны выполняться на любых данных.

Location: USA - Remote Workplace: Remote About Us Since 2013, we’ve been building a CRM that gets out of your way and helps your team sell more, faster. Now we’re building AI into every part of it, so Close does the busywork and your team does the selling. No manual data entry, no 10-click workflows. Just communication-first, AI-powered sales software designed to help you succeed and scale. We're bootstrapped and profitable which means we answer to our customers and play by our rules. We're proud of our 130-person, 100% remote team, focused on building Close so that no small, scaling business fails because it can't figure out sales. ABOUT THE ROLE Close is a CRM built around the communication tools sales teams use every day: email, calling, SMS, workflows, reporting, and AI. Underneath that product is a broad technical surface — Python services and a large application backend, a TypeScript and React frontend, public APIs, Docker and Kubernetes, AWS infrastructure, and integrations with providers that handle sensitive customer data. Security work happens across it all today, but the ownership is spread across Engineering, Infrastructure, and Security & Trust. We’re hiring our first dedicated Product Security Engineer to make that work systematic. You’ll report to the Backend Platform team manager within EPD (Engineering, Product, and Design), while working across the entire product and infrastructure surface. You’ll find vulnerabilities, determine which findings matter most, and drive them through remediation. Often you’ll fix the problem yourself. Other times you’ll give the owning team a clear reproduction, a practical path forward, and enough context to prioritize correctly. You’ll analyze code, build proof-of-concepts, test running applications, tune or replace noisy tools, and automate the repetitive parts of vulnerability management. This is not a role where you forward scanner alerts and call the queue managed. Product and application security will be your responsibility. You’ll partner closely with our Infrastructure team on cloud security, access, and secrets, and with our Security & Trust Lead on GRC Engineering https://grc.engineering/, compliance (SOC 2) goals, audits, and corporate security. This role is a new one at Close. You’ll have significant room to decide where better tooling, clearer ownership, and a small amount of code can reduce the most risk. OUR STACK Our backend is primarily Python, with Flask and FastAPI services and TaskTiger https://github.com/closeio/tasktiger and Temporal handling much of our asynchronous work. We expose REST https://developer.close.com/ and GraphQL APIs and store data in MongoDB, PostgreSQL, Elasticsearch, and Redis. Our frontend is a large single-page TypeScript application built primarily with React. We bundle with Vite, target modern browsers, and test with Vitest, React Testing Library, Playwright, and Chromatic. The product updates in near real time and uses technologies including WebSockets and WebRTC. Our mobile application is built with React Native. We build and test Docker images in CI/CD and continuously deploy them to Kubernetes on AWS. Our infrastructure uses managed services including EKS, MSK, and ElastiCache, alongside services running on EC2. Terraform and Ansible automate much of the underlying infrastructure, and our containerized local development environment lets engineers run the full system on their own machines. For this role, our stack extends beyond simply backend or frontend: browser behavior, frontend state, API authorization, asynchronous processing, data access, third-party integrations, containers, and cloud configuration can all be part of the same attack path. We love open sourcing our code and ideas on our GitHub https://github.com/closeio and on The Making of Close https://making.close.com/, our behind-the-scenes Product & Engineering blog. Check out our open source projects like SocketShark https://github.com/closeio/socketshark, TaskTiger https://github.com/closeio/tasktiger, LimitLion https://github.com/closeio/limitlion and ciso8601 https://github.com/closeio/ciso8601. AI is both how we build and what we ship, and that's reshaped what engineering looks like. This is a transformation we’re embracing and find deeply exciting. YOU ARE - An application security engineer who writes code. You can move from reading an unfamiliar code path, to reproducing an exploit, to proposing or shipping a production-quality fix. Strong Python or TypeScript experience would be especially useful; fluency across both backend and frontend systems is even better. - Skilled at finding vulnerabilities conventional scanners may miss. You use modern AI-assisted review pipelines, guided by expert judgment, to uncover subtle flaws in web apps and APIs—from authentication, authorization, and tenant isolation to injection, SSRF, unsafe data flows, and business logic. You can threat-model designs, white-box review code, and test running systems. - Offensive-minded and operationally responsible. You know how to test like an attacker without being careless with customer data or production systems. You can turn a finding into a safe reproduction, assess exploitability and business impact, and retest the eventual fix. - An automation builder. You have worked with some mix of SAST, DAST, software composition analysis, container scanning, secrets scanning, or cloud posture tooling. More importantly, you know how to tune tools, connect them to engineering workflows, and remove noise. - AI-native and accountable. You use coding agents and LLMs to accelerate investigation, code review, and repetitive engineering work, but you verify their output. You think carefully about what happens when agents clone untrusted code, install dependencies, or receive access to credentials. - Able to separate severity from priority. A score is an input, not a foregone conclusion. You consider reachability, existing controls, customer impact, and attack chains, then explain the risk in language that is legible to an engineer or business owner. - Comfortable working across the business. You’ll collaborate with product engineers, Site Reliability Engineers, Security & Trust Lead, auditors, and external researchers without confusing partnership for pass-off ownership. You will follow findings to closure even when another team is responsible for the fix. - Self-directed in a remote environment. You can take an ambiguous surface (say, secret rotation or dependency remediation) and learn how it works across multiple systems then turn it into a practical plan with measurable progress. You do not need to arrive as the deepest expert in every part of this scope. You do need to be able to investigate an unfamiliar system, determine what matters, and bring the right people with you. YOU WILL The work spans hands-on application security, security automation, vulnerability management, and infrastructure partnership. Depending on where you find the greatest risk and leverage, projects could include: - Build a recurring product security review program. Threat model new features, audit high-risk areas, review code, and build safe proof-of-concepts in isolated development environments. Work across our backend, frontend, APIs, and customer-facing integrations. - Improve application security testing. Combine static analysis, dependency and secrets scanning, dynamic testing in development, and carefully scoped production testing. Use existing tools where they fit and build focused automation where they don’t. - Own vulnerability intake and remediation. Triage findings from HackerOne, scanners, penetration tests, audits, customers, and internal research. Reproduce issues, assess exploitability and impact, track remediation, and verify fixes. Serve as technical lead for our bug bounty program while contract and budget ownership remain elsewhere. - Turn security alerts into useful engineering work. Verify scanner coverage and automate ingestion, deduplication, enrichment, prioritization, and routing—so teams spend less time interpreting alerts and more time fixing important issues. - Make dependency remediation safer and less manual. Improve scanning across our Python and TypeScript codebases, then build workflows to assess upgrades, stage pull requests, run checks, and route work without exposing credentials to untrusted packages or build steps. - Make secrets routinely rotatable. Partner with service owners and Infrastructure to inventory application secrets, add graceful rotation paths, document provider-specific runbooks, and automate rotation where the provider and risk justify it. Expand our use of Vault-backed dynamic credentials and reduce the number of rotations that require a coordinated fire drill. - Strengthen AWS security with Infrastructure. Evaluate and improve automated detection of risky configuration across identity, networking, compute, storage, containers, and registries. Turn findings into secure defaults, just-in-time access patterns, infrastructure guardrails, and actionable remediation—not build a second Infrastructure team. - Support audits and raising the security floor. Partner with Security & Trust on external assessments, provide technical context, and ensure findings are fixed rather than rediscovered. Along the way, create documentation, paved roads, and lightweight training that helps engineers make safer choices without waiting for a security review. - Take a key technical role in security incident response. Partner with Engineering and Infrastructure to coordinate investigation, containment, and remediation. Contribute to root-cause analysis and follow-up improvements, translating lessons learned into stronger controls and reduced recurrence. Tech you’ll touch: Python, TypeScript, React, Flask, FastAPI, GraphQL, Docker, Kubernetes, AWS, Vault, GitHub Actions, MongoDB, PostgreSQL, Redis, Kafka, Elasticsearch and the security tooling you help us choose. BENEFITS - Compensation: Competitive pay plus an organization-wide goal-based bonus - Paid Time Off: ~5 weeks of PTO to start. Plus a 1-week all-company Winter Holiday Break and paid US holidays. You'll earn 2 extra days for every year you're with Close. - 80% Work Option: Work with your manager to choose between a standard 5-day week or a 4-day week at 80% pay - Parental Leave: Paid leave for primary and secondary caregivers - Sabbatical: A 1-month paid sabbatical every 5 years with the team - Healthcare (US residents): Two medical plans with Close covering the majority of your premium, plus Dental, Vision, HSA, FSA, and company-paid Long-Term Disability - 401k (US residents): We match your contributions up to 6%, vested immediately OUR VALUES Build a house you want to live in - Examine long-term thinking and action No BS - Practice transparency and honesty, especially when it’s hard Invest in each other - Build successful relationships with your coworkers and customers Discipline equals freedom - Keep your word to yourself and others Strive for greatness - Constantly challenge yourself and others LEARN MORE Listen to our CEO and Founder, Steli Efti, tell the story of Close’s journey in the $0-30m Blueprint https://www.close.com/blueprint.  Watch our culture video https://www.youtube.com/watch?v=maXKi1GN2MI from our 2023 team retreat in Milan. Every year our entire team gathers in person to build connection, foster cross-functional collaboration, and have fun. In 2027, we're headed to Dusseldorf, Germany! Explore our product. Check out a demo https://www.close.com/demo-site! OUR HIRING PROCESS We ask a few role-specific questions as part of our application process. These questions are designed to help us learn more about you from the start, so please answer each one thoughtfully. We see this as an opportunity to get to know you beyond your resume. We use AI tools daily at Close and expect candidates to do the same. In evaluating your application, we aim to get a sense for you - the way you think, how you communicate, the work you've done. Applications that read as fully AI-generated will not be considered. Regardless of fit, you can expect to hear back from our team with an update on the status of your candidacy. If you progress to the interview process, you'll receive a full outline of the role-specific steps in your first touchpoint with us. We do our best to make the hiring process clear and human.

Location: Oakland, California, United States, AMER From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role Fivetran + dbt Labs is building data pipelines to power the modern data stack for thousands of companies. We’re looking for a Senior Staff Systems Engineer, Data and Integrations to join our Systems Engineering team and set the technical direction for the data that runs Fivetran's business. In this role, you will own the data architecture behind our marketing, sales, billing, and product operations: the canonical data models, the contracts between systems, and the pipelines and transformations that move data reliably between them. You will lead our largest and most consequential data initiatives, such as system migrations, org consolidations, and re-platforming of core integrations, from design through validation and cutover. This position sits at the crossroads of data engineering, data modeling, and business process. You will partner closely with our Systems, Analytics, and Engineering teams, as well as Marketing, Revenue Operations, Accounting, Product Operations, and other business partner teams, and you will mentor the engineers who build within the standards you set. This is a full-time position based out of our Oakland, California office. Technologies You’ll Use Our core systems are Salesforce, Netsuite, Coupa, Workday, and Zendesk, with BigQuery as our data warehouse. Our current integration stack includes Celigo and Fivetran itself.  You should be an expert in SQL and strong in a general purpose programming language such as Python or TypeScript, and comfortable evaluating and adopting new tools when necessary. A data engineering background is required, with expertise in data modeling, ETL/ELT development, data quality testing, and data validation at scale. Experience with dbt or a similar transformation framework, and with API-based and event-driven integration patterns, is preferred. Help us bring established data engineering practices to internal business systems, and define what those practices should be here. What You’ll Do Data Architecture and Standards Own the canonical data models for Fivetran's marketing, sales, billing, and product operations integrations, and define how business concepts map to data across our core systems. Define team-wide standards for data modeling, data quality, testing, governance, and documentation, and drive their adoption across Systems Engineering and partner teams. Contribute to the design of integration architecture, establishing guidance for when to use batch, real-time, and event-driven data movement. Delivery of Complex Initiatives Lead the design and execution of our most complex data initiatives, including bulk migrations, system consolidations, and re-implementation of core integrations, from target-state design through validation, cutover, and stabilization. Build, review, and ship the SQL and Python transformations and pipelines behind these initiatives, setting the bar for code quality on the team. Design the validation and reconciliation approach for migrations and pipeline changes, and sign off with stakeholders that record counts, values, and business rules reconcile. Reliability and Observability Design the monitoring, alerting, and data quality framework that gives end-to-end visibility into data freshness and accuracy across systems, and define the KPIs used to measure integration and data health. Lead root cause analysis on the most complex cross-system data issues, and drive the systemic fixes that prevent recurrence. Business Partnership Technical Leadership Translate ambiguous requirements from cross-functional business partners into data models and technical designs, and drive alignment across teams with competing priorities. Serve as the technical lead and subject matter expert for business data within the Systems Engineering team. Mentor other engineers and review their designs and code, raising the team's proficiency in data modeling, testing, and pipeline design. Write and maintain design documents and data flow documentation for current and target state, so decisions are legible to the team and to partners. Skills We’re Looking For 10+ years of experience in Data Engineering, Analytics Engineering, or a similar role, with a deep focus on modeling and transforming business data and a track record of technical leadership on complex, multi-team initiatives. Expert SQL proficiency, including complex transformations, performance tuning, and large-scale data reconciliation. Strong proficiency in a general purpose programming language such as Python or TypeScript, with experience building production-grade, tested data pipelines. Hands-on experience with business systems data models such as those for Salesforce, NetSuite, Coupa, Workday, or Zendesk, including a data migration, org merge, or major re-implementation. Demonstrated experience designing and delivering large-scale ETL/ELT solutions and the data quality, validation, and governance frameworks around them. Ability to evaluate trade-offs between short-term delivery and long-term data architecture health, and to communicate those decisions clearly. Ability to lead through influence, driving alignment across technical and non-technical stakeholders without direct authority. Bonus Skills Experience with dbt or a similar transformation framework. Hands-on experience with iPaaS platforms such as Celigo, Workato, or Boomi, and with reverse ETL tools, including experience choosing between them. Experience with cloud platforms such as AWS or GCP, infrastructure as code, and CI/CD for data pipelines. Familiarity with AI/ML capabilities to augment data quality, matching, and automation. By stepping into this role, you will define how Fivetran's + dbt Labs business data is modeled, governed, and moved, and lead the initiatives that make it scale. #LI-HYBRID #LI-VA1 The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role.  Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Oakland Pay Range $202,787 — $253,483.50 USD Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . 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