Вакансии

Location: Vancouver, BC Senior Analytics Engineer The Data Science & Analytics team at Asana is how the company turns data into decisions — defining the questions that matter, surfacing the answers, and making sure insight is at the center of every critical product and business call . As a Senior Analytical Engineer, you sit at the intersection of Data Engineering, Analytics, and Data Science, and you own the data foundations for a business domain end to end. Your mandate is to turn raw data into reliable, business-ready datasets that PMs, analysts, data scientists, and leaders actually trust and use — and to define the business logic and metric standards that make AI-powered self-serve trustworthy. You consume governed Silver tables and produce the Gold layer and semantic layer beneath Asana's most important metrics, dashboards, and Genie spaces. This role is based in our Vancouver office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . What you’ll achieve Own the Gold layer for a given business domain (e.g., PLG funnel, marketing attribution, revenue, NPI/AWM): Design and continuously improve the curated, dimensional data models that downstream dashboards, Genie spaces, and ELT reporting depend on. Implement the canonical business logic behind your domain's core KPIs: Translate KPIs into governed, versioned metric marts that resolve "this number doesn't match" disputes for good. Build and curate the semantic layer and Genie spaces that power self-serve in your domain: Author the metadata, documentation, and prompt/metric definitions that let stakeholders query governed data in plain language through Claude and Databricks Genie. Own the metric dictionary for your domain: a single source of truth for what each metric means, who owns it, and where to find it. Partner with peers across DS&A to keep KPI definitions consistent where domains overlap. Author data contracts and SLAs at the Silver→Gold boundary, partnering with Horizontal Data Engineering on the inputs you depend on, and owning data quality, freshness, and oncall for Gold/metric-mart failures in your domain. Build and maintain certified, board-ready dashboards on governed Gold data, partnering with Data Science to translate insight requirements into trusted, reusable products rather than one-off builds. Partner directly with Product & Business, Data Science, and Engineering to turn ambiguous, underspecified questions into scalable datasets — anticipating downstream reporting impacts before they become incidents, and raising the data-model quality bar across the domains you touch. About you Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making . 4+ years in analytics engineering, data engineering, or a closely related analytics role, with a track record of independently owning the data models a team relies on for decisions . Advanced SQL and strong data modeling fundamentals: dimensional modeling, star/snowflake schemas, slowly changing dimensions, and semantic layer design. Hands-on experience with a transformation framework (dbt or equivalent), orchestration tooling (e.g. Airflow), version control (Git), and modern warehouse/lakehouse platforms (Databricks experience preferred). Practical experience with data quality testing and observability, schema management and data contracts, and query/model performance and cost tuning. Demonstrated domain fluency in at least one business area (e.g. PLG funnels, SLG pipeline, marketing attribution, Product telemetry, revenue/ARR) and the judgment to translate "I don't trust this number" into a specific, durable model fix. Strong cross-functional partnership skills: requirement gathering, prioritization, documentation and enablement, driving alignment on metric definitions, and explaining technical tradeoffs to non-technical partners . Curiosity about AI-native a nalytics — NL2SQL, metadata/semantic layers for self-serve, and using tools like Claude and Genie to multiply your reach rather than replace rigor. Exposure to Unity Catalog, Looker/LookML, or reverse-ETL/activation (Salesforce, Marketo, Gainsight) is a plus At A sana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission . If you're interested in this role and don't meet every listed requirement, we still encourage you to apply . What we’ll offer Generous, transparent and fair compensation system (base salary and RSUs) Health insurance with dental Breakfast and lunch catering on the da ys that you work from the office Home office setup budget Gym/Fitness card Fertility healthcare and family-forming support with Carrot Mental Health Support in Modern Health Group life insurance MacBo oks with all necessary accessories For this role, the estimated base salary range is between $106,000 - $120,000 CAD annually . The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process . The listed range above is a guideline, and the base salary range for this role may be modified . In addition to base salary, your compensation package may include additional components such as equity and sales incentive pay (for most sales roles), and benefits . If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role . #LI-Hybrid About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to 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 law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

QA auto (Data Governance / Data Catalog) IT Вакансии В команду крупного банка ищем инженера по автоматизации тестирования для работы с платформой OpenMetadata. Предстоит проверять процессы сбора и обновления метаданных, интеграции с различными СУБД, корректность отображения информации в каталоге и стабильность автоматизированных процессов.

-Разрабатывать и развивать ETL-системы, которые обеспечивают данными различные предметные области: продажи, учёт, логистику. -Анализировать данные и проектировать структуры данных под аналитические потребности различных бизнес-подразделений.

Обязанности: Функциональное тестирование OpenMetadata, включая процессы сканирования источников данных, профилирования данных и управления тегами и глоссариями. Тестирование интеграций с различными СУБД и проверка соответствия метаданных в источниках информации, отображаемой в каталоге.

Location: Poland; UK; Portugal Workplace: remote 1inch is the DeFi ecosystem building financial freedom for everyone. 1inch products help users and builders trade, hold and track digital assets - with the self-custody, comprehensive security and the intuitive user experience they need to unlock the potential of true crypto ownership. 1inch protocols and APIs provide core infrastructure across the DeFi industry and beyond. So if you're someone who thinks big, moves fast and wants to make an impact right from day one, then get ready to join our industry-changing team. Your mission As Data & Analytics Lead, your mission is to turn complex business and product questions into reliable, actionable answers. You will combine AI, data analytics, data engineering, and deep DeFi expertise to build a more intelligent and scalable approach to decision-making. You will use AI not just to accelerate existing analytics, but to rethink how we explore data, test hypotheses, identify patterns, and make insights accessible across the organization. You will be highly hands-on, with expert-level Dune capabilities and a strong understanding of DEXes, DEX aggregators, on-chain data, liquidity, routing, and market dynamics. What you’ll do Create intuitive ways for teams to explore trusted data using AI, natural language, dashboards, and other analytical interfaces. Build AI-enabled workflows and agents that accelerate analysis, uncover insights, and reduce repetitive analytical work, ensuring AI-generated answers are grounded in trusted data, transparent, and verifiable. Turn complex and ambiguous business and product questions into structured analyses, clear insights, and actionable answers. Develop metrics and analytical frameworks that connect user behavior, product performance, on-chain activity, market dynamics, and business outcomes. Proactively identify trends, anomalies, opportunities, and risks, and establish standards for analytical quality, metrics, dashboards, and decision support. Design and evolve data architecture, models, pipelines, and transformations, integrating on-chain and off-chain data into reliable, scalable, and reusable data products. Ensure data is accurate, well-structured, documented, discoverable, and accessible to people and AI systems, with strong standards for quality, observability, maintainability, and performance. Use Dune at an expert level to investigate DEX aggregators, DEXes, swaps, liquidity, routing, users, protocols, and markets, building reusable on-chain datasets and analytical models. Combine blockchain, product, and business data to create a comprehensive view of users, ecosystem activity, and market dynamics, and continuously explore new data sources and analytical approaches. Who you are Deep understanding of DeFi and blockchain data, particularly DEXes and DEX aggregators, including swaps, liquidity, routing, transactions, events, traces, and smart-contract interactions. Expert-level Dune skills, with advanced SQL proficiency and demonstrated experience building sophisticated on-chain queries, datasets, dashboards, and analyses. Strong AI-native way of working, with advanced hands-on experience using Cursor to accelerate analytics and engineering, automate workflows, and build AI-enabled data solutions. Strong proficiency in Python for data analysis, data processing, automation, and AI-enabled workflows. Hands-on experience building and operating modern data platforms with ClickHouse and Airflow, including data modeling, pipelines, transformations, data quality, and observability. Proven ability to turn ambiguous business and product questions into structured hypotheses, robust analyses, and clear, actionable answers. Nice to haves Experience working directly within a DEX, DEX aggregator, DeFi protocol, or other data-intensive Web3 product. Experience working with raw multi-chain blockchain data, including decoding contracts, events, traces, and transactions. Experience applying statistical methods, experimentation, forecasting, or anomaly detection to product and business questions. A strong public track record in the DeFi data ecosystem, such as high-quality Dune dashboards, research, open-source contributions, or community analytics.

• Сопровождение и эксплуатация Data Lake платформ; • Поддержка S3/Object Storage инфраструктуры;

- Разработка автотестов на Python (pytest/unittest) от 5 лет. - Опыт с CI/CD (Jenkins, GitLab CI).

Задачи: — Разработка новых и поддержание существующих отчётов BI-аналитики; — Оптимизация процессов загрузки и трансформации данных; — Коммуникация со смежными отделами по вопросам BI, анализ и уточнение требований; — Разработка макетов для согласований с бизнес-заказчиком, внесение корректировок, проверка достоверности расчетов; — Документирование разработанных отчетов с описанием процессов и процедур. Требования: — Опыт работы MS Power BI (Power Query, Power Pivot, Dax, M), Oracle BI; — Опыт построения сложных отчётов и дашбордов на основе больших объёмов данных; — Понимание работы с MS SSIS, Apache NiFi, Apache Airflow и/или другими ETL-инструментами; — Работа с большими объемами данных; — Опыт работы с СУБД: Oracle, MS SQL; — Аналитический склад ума и внимание к деталям. Условия: — Офис в г. Москва; — График 5/2, пятница - сокращенный рабочий день; — Официальное трудоустройство в аккредитованную IT-компанию; — Работа в структуре крупного холдинга; — Полное соблюдение ТК РФ; — Огромные возможности для самореализации и совершенствования своих навыков; — Внутренняя электронная база знаний; — Профессиональный и карьерный рост, корпоративное обучение.

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . We are looking for a talented and driven individual to be a key part of our Analytics Engineering team within the Data Science organization. We are looking for someone who can work closely with Data Scientists and Engineers across diverse areas of the organization (Consumer, Ads, and Marketing) to curate, develop, and deploy the right data and analytic tooling to drive Reddit’s product forward and provide a data and tooling foundation that will last decades. Your work will empower thousands of your colleagues to improve the user experience and grow our consumer base. Successful candidates have a strong track record of understanding and deeply caring about the purpose of data to support business goals, and can act as an effective conduit between Data Producers and Data Consumers. This role sits at the intersection of Data Science and Data Engineering, and the ideal candidate has skills, experience, and passion in both areas. Responsibilities: Be a key contributor and collaborator to the success of data quality, performance, reliability, and automation initiatives. Manage a portfolio of data products that deliver high-quality, trustworthy data Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. Work closely with engineering to ensure the quality and reliability of these data pipelines. Develop and implement data quality checks, conduct QA and implement monitoring routines Create and manage new data integrations across internal and external systems Create tools and applications for internal use that streamline data analysis and reporting. Drive widespread adoption of these tools and applications with a relentless focus on automation, consistency, and reliability. Serve as a thought partner for data scientists, engineering managers, and leadership on data foundations, communicating and shaping the data foundations roadmap and strategy for Reddit. Qualifications: Bachelor's degree in computer science or a quant educational field 3+ years of experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable code and systems (Python preferred) in a production environment. Strong programming proficiency in Python, SQL, Spark, Scala, etc. Experience with data modeling, ETL and ELT concepts, and patterns for efficient data governance. Experience with manipulating massive-scale structured and unstructured data. Experience with data workflows (such as Airflow), data modeling, front-end or back-end engineering. Experience in data analysis and dashboard design. Deep understanding of technical and functional designs for relational and MPP Databases. Proven track record of cross-functional execution and collaboration. Agentic AI-assisted development experience. Excellent communication skills to collaborate with cross-functional stakeholders at all levels of the company, of differing levels of technical acumen. Self-starter, ability to work independently and autonomously, as well as part of a team. Check out our r/RedditEng post to learn more about the team, and what we do: https://www.reddit.com/r/RedditEng/comments/1mnmf71/analytics_engineering_reddit/ Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave #LI-Remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $164,200 — $229,990 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Задачи: — создавать AI-агентов и платформы для них; — строить MLOps-инфраструктуру; — работать с данными для ML. Требования: — опыт работы в роли MLOps Engineer, Data Engineer или Python ML от 3,5 лет; — production-опыт с фреймворками MLOps: Kubeflow, MLflow, Airflow для оркестрации, понимание их интеграции в CI/CD пайплайны; — опыт работы с Docker и Kubernetes (в контексте развертывания моделей как сервисов); — опыт работы с одним из major cloud-провайдеров (желательно GCP или AWS/Azure с пониманием hybrid-cloud); — умение работать с большими данными, опыт с Greenplum или аналогичными MPP-системами (Teradata, Exasol); — знание распределенных вычислений (Spark); — опыт работы с LangChain/LlamaIndex, FastAPI, знание фреймворков для работы с LLM (Hugging Face, vLLM и т.д.); — отличные знания Python, SQL на очень высоком уровне для работы с data vault; — знания Git, GitLab CI/CD. Условия: — хорошая зарплата, уровень обсуждается индивидуально, есть доплаты за менторство и профактивности; — долгосрочные проекты от российских заказчиков, возможность менять направления, прозрачная система Performance Review; — релокейт между офисами, выбор формата работы (удалённо, офис, гибрид), адаптация для новых сотрудников; — доступ к корпоративному порталу, митапам, конференциям (и как гость, и как спикер); — социальный пакет: ДМС со стоматологией, частичная компенсация спорта, бесплатный английский, оплачиваемый отпуск и больничные; — корпоративная жизнь: тимбилдинги, детские праздники, внутренние мероприятия; — офисы в Москве, Санкт-Петербурге, Казани, Нижнем Новгороде, Самаре.

Задачи: — вести сбор требований с бизнес‑стейкхолдерами — проектировать модели данных по паттернам medallion‑архитектуры (bronze/silver/gold) — строить и оптимизировать ETL/ELT‑пайплайны с dbt — настраивать проверки качества данных (Great Expectations) — оптимизировать Spark‑джобы под SLA — диагностировать проблемы в многосистемных пайплайнах — поддерживать документацию и runbook’и Требования: — от 5 лет опыта в Data Engineering — продвинутое владение Python, Spark и SQL — опыт работы с AWS и Databricks — знание Kafka и инструментов современного Data‑стека (dbt, Airflow или аналогов) — понимание dimensional‑моделирования (star/snowflake‑схемы) — понимание принципов проектирования хранилищ данных и архитектур (lambda, kappa, lakehouse) — умение структурировать задачи для работы с ИИ‑ассистентами — знание топологий систем — уровень английского — Intermediate и выше.

Location: New York City, New York, United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. About Tavily (Acquired by Nebius) In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. Tavily provides the search and intelligence layer that powers AI agents and retrieval systems with trustworthy, real-time information. We work with some of the most innovative teams in AI, from fast-growing startups to global enterprises, helping them build agents that are not only intelligent, but informed. The role We're looking for a Business Analyst to partner closely with our Finance and Sales teams and turn data into decisions. You'll be the owner of the company's most important metrics: revenue (ARR/MRR), bookings, pipeline, conversion, net revenue retention, gross margin and more. Beyond reporting the numbers, you'll uncover the drivers behind them, build the analyses that shape planning and go-to-market strategy, and help leadership answer the critical questions: This is a high-ownership, hands-on role for someone who is as comfortable in a board-deck conversation as in a SQL editor, and who ships analysis that changes what the business does next. Your responsibilities will include: Own the company's core business metrics end-to-end: define them, build the single source of truth, and make sure Finance, Sales, and leadership are all looking at the same numbers. Partner with Finance on revenue recognition, forecasting, budgeting, and board/investor reporting; turn usage and billing data into reliable financial views. Partner with Sales on pipeline health, funnel conversion, win/loss, sales cycle, quota attainment, territory and segment performance, and compensation analytics. Proactively monitor key business metrics, investigate trends and anomalies, and surface actionable insights to stakeholders before they ask. Build and maintain revenue and pipeline models that connect product usage and billing data. Write production-quality SQL and Python to model data, automate recurring reporting, and run analyses at scale. Translate findings into clear recommendations and drive alignment across Finance, Sales, and leadership. Support strategic initiatives: pricing and packaging changes, segment strategy, capacity planning, and go-to-market experiments, with before/after impact measurement. We expect you to have: 5+ years of experience as an Analyst, of which 2+ years of experience as a Business Analyst, FP&A analyst, Revenue/Sales Operations analyst, or equivalent. 2+ years working in a SaaS company; you understand ARR, bookings, NRR, CAC, payback, pipeline coverage, and the metrics that drive a SaaS business. Hands-on experience supporting Finance and/or Sales teams, with a track record of owning metric definitions that the company relies on. Strong SQL and comfort working with large, messy datasets across different sources. Hands-on experience using Python for data analysis and data modeling in a production environment. BSc in Economics / Finance / Statistics / Math / Industrial Engineering or equivalent. Familiarity with modern data tooling (Snowflake/BigQuery, dbt, BI tools like Omni/Looker/Tableau). It will be an added bonus if you have: Experience at an API-first, developer-focused, usage-based, or PLG (product-led growth) company. Experience with usage-based billing and revenue recognition (Stripe, Metronome, NetSuite). Experience with CRM analytics (HubSpot, Salesforce) and sales compensation / quota design. Statistical foundation for experimentation and causal inference. Experience with Airflow or similar orchestration tools. MBA or MSc in a quantitative field. Key employee benefits in the US: Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 401(k) plan: Up to 4% company match with immediate vesting. Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote work reimbursement: Up to $85/month for mobile and internet. Disability & life insurance : Company-paid short-term, long-term and life insurance coverage. Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $179,000 — $224,000 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Задачи: — Тестирование DWH: понимание слоёв хранилища (staging, core, витрины), доменной модели — Тестирование Airflow: чтение логов, анализ падений задач, проверка ретраев, backfill и идемпотентности — Понимание OLAP-подхода: кубы, меры, измерения, агрегаты; опыт проверки данных через Cube REST API — Сверка данных между системами (счётчики, контрольные суммы, полнота) — Негативное тестирование потоков данных и интеграционных обменов Требования: — Опыт работы в QА: от 5 лет — Опыт автоматизации тестирования на Python от 4-х лет — Уверенный SQL: сложные запросы, JOIN, оконные функции, агрегации, работа с большими объёмами данных — Знание Python для автоматизации сверок и анализа логов — Инструменты: DBeaver/SQL-клиенты, Postman/curl, Jira, Confluence, TMS — Тестирование 100% backend — 50% ручное, 50% авто Условия: — full-time — удалённая работа (формат remote)

Location: New York City DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. About the Team The DRW C/Options Data Engineering team is essential to developing valuable datasets and scalable data infrastructure critical to our trading operations. We work closely with traders, researchers, and other engineering teams to ensure seamless data flow and accessibility, supporting data-driven decision-making. Our systems are designed to handle large volumes of data, maintain quality and integrity, and provide robust APIs for fast, ergonomic data retrieval. About the Role In this role you will: Collaborate with cross-functional teams to deliver data solutions that support diverse trading activities. Take full ownership of data products, guiding them from initial concept through to stable production. Design, build, and maintain systems for both batch processing and real-time streaming of time series datasets, ensuring high data quality and reliability. Develop APIs and data access methods for fast, intuitive retrieval of historical and live data, working with both new and existing systems. Provide on-call support as needed. Qualifications: A minimum of 2+ years’ experience using at least one of Python, Java, and C++, and can work comfortably in multiple programming languages A track record of working directly with end customers, scoping and delivering production systems in fast-moving and ambiguous environments Ability to dive deep into complex problems, develop intuitive understandings, spot risks early, and minimize complexity Exceptional interpersonal skills - you communicate clearly with stakeholders as well as other engineers, fostering a collaborative, supportive working environment Experience in the financial markets, especially in delta one, store of value, and/or FICC options trading Experience with Linux-based, concurrent, high-throughput, low-latency software systems Experience with pipeline orchestration frameworks (e.g. Airflow, Dagster) Experience with streaming platforms (e.g. Kafka), data lake platforms (e.g. Delta Lake, Apache Iceberg), and relational databases Have a Bachelors or advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or equivalent work experience The annual base salary range for this position is $175,000 $225,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . #LI-BL1

Location: Malta The Wow Are you passionate about data, technology and finding smarter ways to make systems run better? We're looking for a Data Operations Engineer to join our Data & AI organization in Malta, helping operate and continuously improve the data platforms that support our international business. You'll work with modern data technologies, including Snowflake, Apache Airflow and AWS , ensuring reliable data operations while contributing to improvements in monitoring, automation and platform stability. This role goes beyond day-to-day operations. We encourage our engineers to challenge existing processes, explore new technologies and implement improvements that make a real difference. From enhancing observability to developing automation and AI-assisted solutions, you'll have opportunities to actively shape how our data operations evolve. You'll collaborate with experienced Data Engineering, BI and DevOps teams, applying and expanding your technical skills while gaining valuable experience with business-critical data platforms. A taster of what you will be involved with: Data Platform Operations: Ensure the smooth daily operation of our data platforms, pipelines and reporting services, supporting reliable data processing and availability across the business. Operational Improvements: Identify opportunities to simplify processes, improve data reliability, reduce manual effort and enhance the efficiency of our operations. Automation and Innovation: Develop scripts, automated checks and AI-assisted solutions to streamline operational activities and improve platform reliability. Monitoring and Observability: Work with monitoring and alerting solutions, improving visibility into data pipelines and platform health to detect issues before they impact the business. Production Releases and Changes: Support deployments, data processing activities and operational changes, helping maintain stable and reliable production environments. Incident Management and Troubleshooting: Investigate and resolve technical issues, including pipeline failures, data inconsistencies and processing delays, collaborating with engineering teams when needed. Participate in a scheduled, compensated out-of-hours on-call rotation to help maintain service reliability. Cross-Team Collaboration: Work closely with Data Engineers, BI Developers and DevOps Engineers, share knowledge, document solutions and contribute to continuous improvement initiatives. What we are looking for: Must haves: Experience in Data Engineering, Data Operations, production support, database support or a similar technical role. Strong SQL skills , including writing and troubleshooting queries, working with joins and aggregations, investigating data inconsistencies and validating data. Good understanding of data processing concepts, data pipelines, transformations and dependencies. Experience troubleshooting technical issues using queries, logs, monitoring information or other diagnostic tools. Familiarity with production operations, incident management and troubleshooting practices. Strong analytical and problem-solving skills, with a structured approach to investigating issues and identifying root causes. Good written and spoken English, a collaborative mindset, ownership and willingness to learn. Nice to have: Snowflake or other cloud data warehouses , including data processing, querying and troubleshooting. Workflow orchestration, scheduling and data pipeline operations. Cloud environments and cloud-based data services. Monitoring, logging, alerting and observability solutions. Scripting and automation using Python, Bash or similar languages. Production deployments, change management or CI/CD processes. What we offer Much like riding a rollercoaster, sometimes life at Betsson can be lightning fast with twists and turns but always FUN! Then again, what else would you expect from a business 75% millennial and 1700 strong, spread across 7 offices with 900 based out of our Malta HQ alone! We recognise it may not be for the faint-hearted, but if you’re a go-getter, initiator and adrenaline junkie, always striving to push the boundaries and challenge yourself, then you’ll fit right in. Challenge accepted? By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

Задачи: — Разрабатывать и поддерживать ETL процедуры в Airflow — Проектировать, реализовывать и внедрять распределённые системы обработки и хранения данных — Участвовать в развитии архитектуры хранилища — Работать с реляционными/NoSQL базами данных — Разрабатывать и поддерживать процедуры автоматизации аналитической инфраструктуры Требования: — Уверенное знание SQL — Уверенное знание Python — Опыт разработки ETL процедур от 3-х лет — Опыт работы с реляционными СУБД — Навыки командной разработки в Git Будет плюсом: — Современные code-driven ETL/ELT инструменты — Распределенные колоночные СУБД (ClickHouse, Vertica, Greenplum) — Docker, Kubernetes — S3 хранилище — CI/CD процедуры Условия: — Полная занятость — График 5/2 — Формат работы: удалённо

Требования: — Коммерческий опыт построения и развития DWH и data pipelines — Уверенный коммерческий опыт минимум с 3 из 4 инструментов: ClickHouse, Debezium, dbt, Airflow — От 2 лет коммерческого опыта в Data Engineering / DWH — Сильный SQL, включая оптимизацию сложных запросов Важно: — Офис на испытательном сроке, далее гибрид 3/2

Location: Sofia About us The Financial Times is one of the world’s leading news organisations, globally recognised for its authority, integrity and accuracy, with a mission to deliver quality information and services worldwide. At the FT, curiosity thrives and ambitious thinking is rewarded. Here, you’re given the chance to reach millions, create work that matters and deliver impartial journalism in a polarised world. In our warm, collaborative culture, you’ll connect with a diverse community of experts who support your growth, career aspirations and wellbeing. Your future at the FT will be filled with opportunities that challenge and inspire you. With no fixed path, you’ll discover new skills and forge a career that can take you anywhere. Build a newsworthy career at the FT. Our commitment to diversity, equity and inclusion We believe everyone should have a fair opportunity to contribute, succeed, and reach their full potential. That means ensuring everyone is heard, respected, and valued, while identifying and removing barriers that may get in the way. Our commitment is to be an employer role model, grounded in inclusion and fairness for all.We want every application to receive fair and thoughtful consideration; therefore, all applications are reviewed by a member of our recruitment team, not by AI. The role The Analytics Engineer is responsible for bridging the gap between data engineering and data analytics by maintaining and developing scalable data models and solutions that support finance, B2B, and B2C teams. The role plays a key part in delivering value through modern data stack technologies (including dbt), supporting cloud migration efforts, ensuring data quality, and maintaining the performance of analytical data pipelines. Key responsibilities Collaborate with stakeholders across departments to design and implement robust data models and BI solutions. Build, test, and maintain data transformations using dbt (data build tool). Implement software engineering best practices for data, including version control, CI/CD, and automated testing. Deliver day-to-day support and project-related tasks for the data and BI infrastructure. Develop and maintain scalable, maintainable, and well-documented data pipelines. Identify and resolve issues across ETL/ELT processes and data pipelines. Required skills and experience Essential 3+ years of experience in Analytics Engineering, BI, or Data Engineering roles. Strong proficiency in SQL, including complex queries and performance tuning. Hands-on experience with dbt for data transformation and modeling. Understanding of data migration to cloud platforms such as AWS (Redshift) or GCP (BigQuery). Familiarity with database design, version control (e.g. Git/GitHub), and CI/CD practices. Experience with ETL/ELT tools (e.g. Airflow,DBT). Personal skills Strong analytical thinking and problem-solving abilities. Effective communication skills and ability to collaborate across teams. Attention to detail and focus on continuous improvement and data quality. Adaptability to fast-paced environments. Often used technology stacks and tools Databases & Data Warehouses: AWS Redshift, BigQuery, MS SQL Server. Data Transformation: dbt (data build tool). ETL & Data Processing: Airflow. BI & Data Visualization Tools: Looker. Programming & Scripting: SQL, Python. Version Control & DevOps: GitHub, CI/CD pipelines. Cloud Platforms: AWS, GCP. What’s in it for you? Our benefits Annual bonus scheme 25 days paid leave 24/7 Employee Assistance Program Life Insurance Enhanced Parental Leave policy Food Allowance Multisport Card Both in house and external training programs Your own training dedicated budget (for conferences, courses etc.) We currently operate a hybrid model which requires staff to work onsite 50% of the time, subject to role requirements & regular review. While flexible working requests will be considered, not all patterns are suitable for all roles. We believe this balanced approach supports flexibility and protects our culture, making collaboration and communication easier, building stronger relationships and team cohesion, and supporting peer learning.  We reserve discretion on reasonable notice to change this approach either generally or for specific individuals or teams. Accessibility We are a disability confident employer and Valuable 500 signatory. Please let us know if you require any reasonable adjustments/personalisation as part of the application process or to enable you to attend an interview. If you would like to discuss your requirements or have any questions, email talent@ft.com and a member of our team will be happy to help. Further information At the FT, we embrace innovation and the use of technology and appreciate that individuals may leverage AI tools as part of their job application process. Whilst we are happy for you to use AI to assist with your application, it is essential that all information provided is authentic and accurately represents your skills, experience, and qualifications. Candidates should be aware that the use of AI throughout the application process may be monitored to ensure a fair and transparent hiring process for all. Please beware of fraudulent job postings and offers claiming to be from the Financial Times. All legitimate opportunities will direct you to apply through the official Financial Times careers site, and the FT will never ask for financial information, payments, or referrals to third parties during the hiring process. If you have any concerns about the legitimacy of a job posting or suspect any scam activity, please contact talent@ft.com. Interested in the FT but don’t see the right role yet? Join our Talent Community to receive exclusive updates, featured jobs, and insights into working at the FT. #LI-MG1