Дата-инженер вакансии

Ipotekabank — банк в Узбекистане, входящий в международную финансовую OTP Group, специализирующийся на ипотечном и розничном кредитовании. Вакансии: - Senior Software Engineer (AI) - Senior/Middle Data Engineer Офис в Ташкенте.

Задачи: - Разработка и развитие микросервисов и data-процессов для online/streaming и batch обработки - Построение пайплайнов обработки, обогащения и репликации данных - Создание витрин, агрегатов и ML-фичей для антифрод-моделей - Работа с большими объёмами исторических данных и тяжёлыми расчётами - Оптимизация производительности и надёжности сервисов и пайплайнов Требования: - Коммерческий опыт разработки на Python - Опыт создания backend-сервисов и data-пайплайнов, понимание микросервисной архитектуры - Опыт работы с большими объёмами данных, понимание batch и streaming обработки - Опыт работы с реляционными и in-memory базами данных - Понимание принципов работы ML-пайплайнов - Будет плюсом: опыт в Anti-Fraud / Risk / Scoring, low-latency системах; Spark, Kafka, Tarantool или Ignite Условия: - Формат работы: удалённо - Пятница — сокращённый рабочий день

Требуется специалист на вакансию «Инженер данных». Местоположения: Москва, Казань, Нижний Новгород. Полный рабочий день. Требуемые навыки: — middle уровень — SQL — Python — Алгоритмы и структуры данных — PostgreSQL — Базы данных — Apache Kafka

Mycar Digital — цифровой проект для автомобилистов: маркетплейс по продаже и покупке авто, автоматизация бизнес-процессов, автокредитование и дилерские центры. Формат работы: гибрид (Алматы, Казахстан).

Задачи: — проектировать, разрабатывать и поддерживать ETL/ELT-пайплайны — собирать, обрабатывать и трансформировать данные из различных источников — разрабатывать и сопровождать слои DWH, витрины данных и data marts — настраивать интеграцию источников данных: CRM, ERP, BI и внешних сервисов — разрабатывать внутренние сервисы и API на Python — заниматься мониторингом, логированием и устранением ошибок Требования: — практический опыт работы с Python, SQL, Airflow, ETL/ELT и DWH — опыт разработки и поддержки data pipelines — знание реляционных СУБД — опыт работы с API

Location: Kazakhstan; Kyrgyzstan; Uzbekistan Workplace: Hybrid Salmon is a technology-driven financial company building a banking and lending platform across Southeast Asia, starting in the Philippines. We combine global fintech expertise with deep local market knowledge to make financial services simple, accessible, and useful for millions of people across the region. 7M+ app downloads. 2M+ monthly active users. 7,000+ partner stores. US$310M+ raised from leading global investors. Manila-based, globally distributed, and hybrid-first — our team spans 45+ countries. If you want to solve complex problems at scale and impact how millions of people access and manage money, come build with us. Southeast Asia's fintech moment starts here. About the role: You'll build the analytics layer for Finance and Marketing & Growth — two areas that only get partial coverage today — and help shape how analytics engineering scales as the team and data volume grow. What you'll do: - Build the semantic layer that powers Finance's financial reporting, turning business logic into reliable, gold-layer datasets. - Build the analytics layer for Marketing & Growth, enabling self-service reporting on acquisition, funnels, and campaign performance. - Help define how analytics engineering scales across the team — supporting other analysts' data models and shaping technical standards. What you'll own: - Own the semantic layer for financial reporting, ensuring one consistent source of truth for business metrics. - Own the analytics layer for Marketing & Growth, from data modeling to self-service reporting. - Build and maintain dbt models (staging, intermediate, marts) with tests, documentation, and reusable macros. - Design scalable data models in Databricks silver and gold layers, applying dimensional modeling. - Support other analysts across the data team, optimizing self-built data models when performance or reliability issues come up. - Contribute to defining the strategy and standards for analytics engineering as it grows. What makes you a strong fit: - Strong SQL expertise, including complex queries, window functions, and query optimization on large datasets - Hands-on experience with dbt — models, macros, tests, documentation, and CI workflows - Strong dimensional modeling experience (3NF/Inmon, star schema, or anchor modeling) - Experience building semantic layers or maintaining a single source of truth for business metrics - Experience in banking or fintech is a plus, especially data modeling for financial products - Comfortable working in Git-based ELT workflows What we offer: Ownership and flexibility - Stock option plan — four-year vesting with a 25% cliff after the first year - Remote-first role, with collaboration hours from 10:00 Manila time (UTC+8) - Company-provided tools and equipment Health and time off - Medical insurance support for you and your family through co-funding or reimbursement, depending on your location and subject to policy limits - Access to an internal mental health support specialist - 22 vacation days, Philippine public holidays, and 15 sick days Growth and team experience - Opportunities to learn and share your expertise through internal expert meetups, external conferences, speaking opportunities, and industry publications - Company-sponsored trips to Manila to meet and work with your team in person - Regular team offsites, sports activities, and team events - High-performing teams can earn a dedicated beach house week in Southeast Asia We believe strong teams are built by people with different backgrounds, experiences, and points of view. Salmon is an equal opportunity employer, and we make hiring decisions based on skills, experience, and potential.

Задачи: - Развивать корпоративное хранилище данных: проектировать слои, схемы, таблицы и представления, оптимизировать структуру хранения; - Разрабатывать и сопровождать витрины данных для аналитики; - Проектировать и разрабатывать процессы загрузки данных из разнородных источников; - Настраивать потоки передачи данных между системами: интеграции, синхронизация, обработка ошибок; - Строить дашборды, алертинг и мониторинг; - Обеспечивать наблюдаемость пайплайнов: контроль качества данных, отслеживание задержек и сбоев загрузок; - Проводить аудит текущих решений, выявлять точки роста; - Собирать и уточнять требования к данным вместе с аналитиками и бизнес-заказчиками; - Участвовать в анализе данных: выявление зависимостей, построение логических связей, подготовка данных для аналитики. Требования: - 4+ года коммерческого опыта в роли Data Engineer; - Понимание принципов построения DWH (Kimball / Inmon, star schema, ETL/ELT); - Опыт построения систем мастер-данных; - Умение самостоятельно превратить размытую бизнес-задачу в модель данных и план работ. Будет плюсом: - Опыт ответственности за архитектуру хранилища или крупного домена целиком; - Внимание к качеству данных как отдельной задаче: проверки, SLA, договорённости с владельцами источников; - Опыт с ML и Computer Vision. Условия: - Комфортный офис в Mega Alma-Ata с паркингом и видом на горы; - Гибридный формат работы; - Официальное трудоустройство, медстраховка для вас и близких, компенсация фитнеса.

Location: Remote - Global Workplace: Remote About the company Trust Wallet is the secure, self-custody Web3 wallet that empowers people to own and control their digital assets. Whether you're new to crypto or an experienced user, Trust Wallet makes it easier, safer, and more convenient to explore Web3, securely access dApps, manage your crypto, and buy and sell digital assets, all in one place. ABOUT THE ROLE As a Senior Data Engineer, you will play a key role in building and scaling the data platform that powers analytics across Trust Wallet. You'll be responsible for designing, developing and maintaining data pipelines and data models, ensuring a seamless, scalable and reliable flow of data from source systems through to the decisions it supports. Leveraging your experience with Databricks and Spark across both streaming and batch workloads, dbt or a similar transformation framework, cloud infrastructure, and custom solutions in Python, you'll work closely with our data analysts and engineering teams to turn data into a strategic asset for our company. KEY RESPONSIBILITIES - Data Platform Engineering: Architect and maintain robust, scalable and secure data infrastructure on Databricks, covering both streaming and batch workloads. - Data Pipeline Development: Design, develop and maintain data pipelines, primarily in Python and Spark, to automate ingestion and transformation across internal systems, external providers and on-chain sources. - Data Modelling: Design and maintain dimensional data models and transformation layers in dbt, with tests and documented contracts, so metrics are consistent and reusable across the company. - Data Lake Management: Oversee the data lake and lakehouse layers, ensuring efficient storage, effective partitioning, high data quality, and monitoring and alerting that surfaces issues early. - Integration and Customisation: Integrate Databricks with a wide range of data sources, including change data capture from operational databases, third-party APIs and blockchain data, and adapt data flows to specific business needs. - Performance, Scalability and Cost: Optimise pipelines and storage for performance, reliability and cost efficiency at scale. - Data Governance and Security: Apply best practices for governance, security and compliance in cloud and Databricks environments, including access control, encryption and monitoring. - Collaboration and Documentation: Work closely with platform engineers, data analysts and other stakeholders to understand data requirements, and document infrastructure, models and best practices. REQUIRED QUALIFICATIONS - Experience in Data Engineering: 3+ years as a Data Engineer, with hands-on ownership of production pipelines and lakehouse or data warehouse architecture. - Databricks and Spark: Strong practical experience with Databricks, Delta Lake and Spark, including both streaming and batch processing, and the judgement to choose between them. - Data Modelling: Solid understanding of dimensional modelling, slowly changing dimensions and data warehouse design, with the ability to define and defend the grain of the models you build. - Transformation Frameworks: Experience with dbt or an equivalent framework for managing transformations, testing and lineage. - Cloud Proficiency: Strong cloud fundamentals, including identity and access management, object storage, networking and infrastructure as code. We run on AWS; deep experience with Azure or GCP transfers well. - Proficiency in Python and SQL: Comfortable writing production transformations as well as services and connectors. - Data Quality and Governance: Experience implementing testing, monitoring and governance practices in cloud data environments. PREFERRED SKILLS - Experience with change data capture and replication from operational databases - Familiarity with blockchain or on-chain data - Infrastructure as code, ideally Terraform, and CI/CD for data workloads - Experience with BI and semantic layers such as Holistics, Looker or similar - Containerisation and orchestration (Docker, Kubernetes) ADDITIONAL INFORMATION This is a global and fully remote role. You must have the right to work for the country you are based. WHY WORK AT TRUST WALLET? - Be a part of the world’s leading blockchain ecosystem that continues to grow. - Excellent learning and career development opportunities. - Work alongside diverse, world-class talent, in an environment where learning and growth opportunities are endless. - Tackle fast-paced, challenging and unique projects. - Work in a truly global organization, with international teams and a flat organizational structure. - Work fully remotely with flexible working hours. - Enjoy competitive salary and benefits. Apply today to join our team in building the world’s most trusted and secure crypto wallet and enable a decentralized future for everyone. Trust Wallet is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success. *Due to the large amount of the applications, please consider your application as unsuccessful should you not be contacted within 4 weeks from your application date.

Location: European Union; Ukraine Workplace: Remote ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE We are looking for a Data Analytics Engineer to build, optimize, and maintain the analytical data layer that powers decision-making across the organization. You will transform business requirements into reliable, well-modeled datasets using dbt, SQL, and cloud data warehouses (BigQuery, ClickHouse). This role combines data modeling, documentation, data quality design, and close collaboration with analysts, engineers, and product teams to ensure consistent, trustworthy reporting. You will serve as the bridge between raw data ingestion and analytics — shaping how data is structured, validated, and delivered. Responsibilities - Design, build, and maintain dbt models (staging, core, marts) based on business needs - Develop scalable SQL transformations and ensure efficient, cost-effective query performance - Implement data quality tests (dbt tests, custom checks, anomaly detection) and maintain high data reliability. - Create and maintain documentation for datasets, data lineage, business logic, and transformation rules - Collaborate with Data Engineers on improving raw data structures, ingestion patterns, and source readiness - Partner with Data Analysts, Product Managers, and Marketing teams to translate business requirements into clean, reusable data models - Monitor data pipelines and marts, resolve issues, and prevent inconsistencies in reporting - Support governance initiatives: naming conventions, taxonomy, schemas, metric definitions, and standardization - Contribute to continuous improvement of our data modeling frameworks, performance tuning, and technical decision-making Requirements - Strong SQL experience with a deep understanding of analytical modeling concepts - Hands-on experience with dbt (models, tests, docs, macros) - Experience working with cloud data warehouses such as BigQuery or ClickHouse - Understanding of data modeling patterns - Familiarity with data engineering concepts (ELT/ETL, orchestration, version control, CI/CD) - Experience with data quality frameworks or implementing validation logic - Ability to translate complex business processes into clean analytical datasets. - Strong documentation skills and attention to detail - Experience collaborating with cross-functional teams and supporting analysts with reliable data - Knowledge of Python is a plus (but not required) Nice To Haves - Experience with orchestration tools (Airflow, Dagster) - Experience working with marketing, product, or billing datasets - Exposure to metric layers, semantic layer design, or BI governance - Basic understanding of observability tooling (Grafana, Prometheus, ... ) - Experience optimizing BigQuery costs or ClickHouse performance LOCATION Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours. BENEFITS Discover the perks of being part of our vibrant team! We offer: - Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance. - Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days. - Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge. - Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them. - Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere. Read more about it here: https://docs.google.com/document/d/1nkrN76JlZkbKj9WSOhlT1_mni_CZeDkHdwfIjPXVwvk/preview?tab=t.0#heading=h.ndsdl4wapxtt Be part of our fast-growing team and seize this excellent opportunity for personal and professional growth! INTERVIEW PROCESS After submitting your application, we conduct a thorough review which typically takes 3 to 5 days, but may occasionally take longer due to the volume of applications received. If we see a potential fit, we proceed with the following steps: - Recruiter Screening (40 minutes) - Technical Interview (90 minutes) - Final Interview (60 minutes) LIFE AT RUBY LABS At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day. This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen. Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success. #LI-Remote

Задачи: — Участвовать в формировании модели данных — Проектировать и разрабатывать витрины и потоки данных на основе потребностей бизнес-пользователей — Участвовать в проектах по развитию Data Platform — Писать скрипты SQL и Python (опционально) — Прорабатывать интеграции с внешними системами для Data Platform Требования: — Свободно владеть SQL — Опыт работы с DWH в качестве аналитика или разработчика минимум 5 лет — Понимать теорию СУБД и ETL-процессов — Знание Python или другого языка программирования — Опыт проектирования объектов БД на основании бизнес требований Условия: — Работа в офисе или удаленно по договоренности — Платформа обучения и развития «Т‑Банк Апгрейд» (курсы, тренинги, вебинары, базы знаний) — Поддержка менторов и наставников, помощь в карьерном развитии — Оформление полиса ДМС со стоматологией и страховки от несчастных случаев — Льготное страхование близких — Возможность работы в аккредитованной ИТ-компании — Льготные тарифы на продукты Т‑Банка — Частичная компенсация затрат на спорт — Well-being-программа для улучшения психологического и физического здоровья, а также юридической и финансовой поддержки — Три дополнительных дня отпуска в год — Достойная зарплата, обсуждаемая на собеседовании

Location: Remote USA Workplace: remote ABOUT YOU We are looking for a Head of Fund Analytics & Automation who is a hands-on builder, rigorous with data, and fluent in finance conversations to join our Credit Fund team in the office of the Chief Credit Officer. The best candidate will be someone who thrives in a fast-paced, highly collaborative, and exceptionally dynamic setting and is excited to design, build, and operate the fund's entire data and automation stack end to end — and then own it as the fund goes live. The credit fund is being built with a deliberately small team. Instead of hiring several analysts and operations staff, we want one senior technical hire who can do both: engineer the platform and sit across the table from investors and borrowers. Underwriting here is built on real payment telemetry — including Xsolla transaction data — and that data edge is the foundation of this role. Strong SQL, Python, and production automation skills are essential, along with real experience in portfolio analytics, market risk, or credit. The ability to ship audit-grade systems and then defend the numbers in front of LPs and borrowers will be key to your success in this role. The role starts as a builder and becomes the owner-operator of the platform, with a growing seat in underwriting decisions and, as the platform and deal volume grow, scope to hire and lead a small team. If you're passionate about applying AI-governed automation to private credit and love building the systems that let a lean team punch far above its weight, we would love to hear from you! ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. Responsibilities First 6 months — priorities in order - Deal pipeline live: origination intake through credit committee, with the full audit trail. - Scoring data layer: borrower financials and payment telemetry ingested, stored, and under documented data contracts. - LP / fundraising pipeline instrumented, and first investor reporting shipped. Explicitly out of scope: legal documentation, fund administration, and accounting — these sit with external providers. Phase 1: Build (through first close) Deal pipeline management - Design and run the full deal workflow: origination intake, screening, scoring, credit committee, closing. - Implement it as governed automation (workflow orchestration such as n8n or similar, with LLM-assisted steps where they add value): every automated output validated against a defined schema, low-confidence results routed to human review, and a complete audit trail suitable for LP due diligence. Scoring and underwriting data layer - Build the ingestion and storage layer for borrower financials and payments telemetry (including Xsolla transaction data) — PostgreSQL or equivalent, ETL pipelines, materialized views, documented data contracts. - Develop credit scoring and forecasting models in Python, with proper train/test discipline, leakage and PII exclusion, and ongoing monitoring for drift and degradation. - Maintain evaluation and regression checks so model and automation quality is measured continuously, not assumed. Fundraising / LP pipeline - Build and operate the investor pipeline: CRM automation, conference and referral pipeline tracking, follow-up orchestration, and data room preparation and upkeep. - Instrument the pipeline so we always know conversion rates, stage aging, and next actions per LP. Investor and borrower dashboards - Ship reporting for both audiences: fund-level metrics for investors, facility-level metrics for borrowers. - Numbers must reconcile to source systems and be reproducible outside the BI tool — audit-grade, not demo-grade. Tableau / Power BI or a lightweight web dashboard, whichever fits. Reliability, cost, and security of the stack - Budget caps and cost monitoring on all AI-assisted automation; regression canaries before changes ship. - Access control and data protection appropriate for fund data: deny-by-default permissions, audit logs, strict handling of LP identities, borrower financials, and deal terms. - Documented runbooks and handover-ready documentation as part of "done" — the stack must be operable by someone other than its author. Phase 2: Operate (post-close) - Move into an operating role on the underwriting side: portfolio monitoring, covenant and collateral tracking, scenario and stress analysis. - Extend the platform to other investment types and support the capital formation team with the same pipeline and reporting infrastructure. Client and investor facing This is not a back-office role. The person will join investor and borrower meetings, present the dashboards and the numbers behind them, and field diligence questions directly. Fluency in finance conversations is as important as engineering. The person will also respond to LP operational due diligence questionnaires on the data and automation stack. Qualifications and Skills Required - 7+ years across data analytics / data engineering, including recent hands-on experience building and running production automation (not prototypes or notebooks). - Proven production experience with LLM-based automation: schema-validated outputs, human review gates, evaluation and regression testing, cost-tiered model routing. - Strong SQL and Python; ownership of a PostgreSQL (or similar) data platform end to end — ETL, materialized views, performance tuning, data contracts. - Workflow orchestration experience (n8n, Airflow, or comparable). - BI and dashboarding: Tableau, Power BI, Qlik, or equivalent web dashboards; a track record of reporting that executives actually used for decisions. - Security discipline for sensitive data: role-based access, deny-by-default policies, audit trails, PII handling. - Finance background: degree in finance or quantitative field plus real experience in portfolio analytics, market risk, or credit — able to hold their own in an underwriting or investor conversation. - Strong written and spoken English; comfortable presenting to senior external audiences. Preferred - Direct exposure to private credit, lending, or fund operations. - Forecasting and statistical modeling track record (capacity planning, SLA/risk forecasting, or similar). - Experience with embeddings / semantic search and multi-model AI setups. - Web development ability (React / TypeScript or similar) for internal tools and dashboards. - Experience in audited or regulated environments (SOC 2, fund audits, or equivalent). Benefits We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes 100% company-paid medical, dental, and vision plans, unlimited Flexible Time Off, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we’re not just building a business; we’re cultivating a community that values creativity, collaboration, and the transformative power of play. Equal Employment Opportunity Statement Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law. We consider qualified applicants with criminal histories in accordance with the Fair Chance Act. Criminal History Consideration For the Head of Fund Analytics & Automation — Credit Fund position, we will conduct a background check that may include the following: Criminal history check Employment verification Education verification Credit history check Relevance to Job Responsibilities The background check is relevant to this position because of the following role responsibilities: Handling sensitive financial information and supporting fund analytics, financial models, and deal data Accessing confidential company data Ensuring compliance with regulatory requirements Rights Under the Fair Chance Act Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact careers@xsolla.com. By submitting the following job application form, you consent to Xsolla processing your data for career-related inquiries and potential employment opportunities. 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Location: Kazakhstan; Kyrgyzstan; Uzbekistan Workplace: Hybrid Salmon is a technology-driven financial company building a banking and lending platform across Southeast Asia, starting in the Philippines. We combine global fintech expertise with deep local market knowledge to make financial services simple, accessible, and useful for millions of people across the region. 7M+ app downloads. 2M+ monthly active users. 7,000+ partner stores. US$310M+ raised from leading global investors. Manila-based, globally distributed, and hybrid-first — our team spans 45+ countries. If you want to solve complex problems at scale and impact how millions of people access and manage money, come build with us. Southeast Asia's fintech moment starts here. About the role You'll build and own the data pipelines and lakehouse architecture that turn raw data into reliable inputs powering products used by millions of people. What you'll do - Design and run batch and streaming pipelines on Databricks and Apache Spark over AWS, ingesting from databases, APIs, and event streams. - Shape our lakehouse architecture on S3 and Delta Lake, including medallion (Bronze / Silver / Gold) layering and storage optimization. - Work directly with analytics, engineering, and product teams to turn raw data into reliable, usable inputs for the business. What you'll own - Own projects end to end — from stakeholder alignment and design review through implementation, launch, and ongoing support. - Build self-service data solutions that let other teams deliver their own data needs, designed to scale and extend easily as new sources and use cases are added. - Build and maintain scalable ETL/ELT pipelines that are fault-tolerant and cost-optimized. - Optimize Spark jobs end to end — cluster sizing, caching, joins, shuffles, partitioning, and storage formats (Parquet, Delta). - Manage Databricks Workflows, jobs, cluster configurations, and the underlying infrastructure — security policies, resources, and access — responding to failures and performance issues. - Implement data governance and access control with Unity Catalog across accounts and environments, including handling of PII. What makes you a strong fit - Hands-on experience with Databricks and strong proficiency in Apache Spark (PySpark and/or Scala). - Strong Python for data engineering, plus SQL and Spark SQL for transformation and analytics. - Experience with Delta Lake and lakehouse architectures, including performance optimization. - Proven ownership — you've run projects where you knew the weak points, gathered feedback, and made your solutions easy to scale and maintain. - Experience writing clean, testable, maintainable code with Git-based version control. - Experience with infrastructure-as-code such as Terraform or Ansible is a plus — not required, and easy to pick up on the job. What we offer Build what's next in Southeast Asian fintech. Ownership and flexibility - Stock option plan — four-year vesting with a 25% cliff after the first year - Hybrid-first, with fully remote work available for eligible roles and core collaboration hours from 12:00 to 19:00 Manila time (UTC+8) - Company-provided tools and equipment - Office in Bonifacio Global City, Manila — a modern, walkable district at the centre of the Philippines' growing tech scene Health and time off - Medical insurance support for you and your family through co-funding or reimbursement, depending on your location and subject to policy limits - Access to an internal mental health support specialist - 22 vacation days, Philippine public holidays, and 15 sick days - 105 days of paid maternity leave and up to 14 days of paid paternity leave for employees relocating to Manila Relocation and family support - Relocation support for you, your family — including flights, two weeks of accommodation, visas, paperwork, and logistics - Reimbursement of eligible pet relocation expenses - US$2,500 per year for flights home - Baby and family stipends for employees relocating to Manila: US$1,000 per month for each child under two and US$500 per month for each child aged two to 18 Growth and team experience - Opportunities to learn and share your expertise through internal expert meetups, external conferences, speaking opportunities, and industry publications - Company-sponsored trips to Manila to meet and work with your team in person - Regular team offsites, sports activities, and team events - High-performing teams can earn a dedicated beach house week in Southeast Asia Considering a move to Manila? See what life with Salmon looks like https://www.youtube.com/watch?v=nYQLKhuZHIE&t=34s

Location: New York; Canada; United States Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a member of our Analytics & Data Insights team, you'll tackle the kind of problems that don't have textbook answers yet, launch products that didn't exist a year ago, and help enterprises understand what foundational AI actually means for their bottom line. As a Data Engineer, you will: - Work directly on new customer experiences built on one of the most advanced AI systems in the world - Collaborate daily with researchers and engineers who are some of the best in the world at what they do - Run implementations end-to-end and see initiatives through to real outcomes - Partner across research, marketing, sales, and finance to help define how Cohere grows, with your recommendations feeding directly into products and strategy You may be a good fit if you have: - 5+ years of experience working on production-grade data processing systems - Strong command of Python and SQL - Experience with distributed data processing frameworks such as Apache Beam, Spark, or Flink, alongside large-scale data system design - The ability to transform unstructured data into performant datasets in relational databases and blob storage - Familiarity with modern analytics stack tooling such as BigQuery, Airflow, or dbt - Knowledge of Java or Golang (nice to have) - Experience with Kubernetes (nice to have) - Genuine excitement about AI - you follow the research, have opinions, and enjoy being in the weeds - Comfort operating at the edge of what's known, with a desire to build something genuinely new rather than optimise what already exists FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Simple Life is the #1 AI-powered health coaching app for adults who want to lose weight and enjoy a healthier lifestyle—without the stress or extremes. Our mission is to empower people to feel their best every day. By challenging traditional, restrictive approaches, Simple offers a more sustainable method grounded in ease, personalization, and real-life support. Simple has had over 17 million downloads and more than 300,000 5-star reviews, having helped millions lose weight successfully and sustainably. Simple has earned recognition as Best Virtual Coach and one of the Top 100 AI companies — all thanks to a dedicated global team driving real impact. With SIMPLE as a partner in their pocket, users feel cared for and empowered to embrace — and stick to — new healthy habits. Simple is looking for a Senior Data Engineer to join our Tech team. Push the pace of innovation and build a future of a healthier world with us! Задачи: — Design, build, and maintain streaming pipelines. — Develop custom ingestion pipelines from third-party APIs, webhooks, and SDKs. — Migrate existing data ingestion pipelines from SaaS tools to our own infrastructure. — Deliver data to the raw layer of our Snowflake warehouse with schema consistency, idempotency, and resilience to malformed or late data. — Evolve the existing AWS streaming stack (Kinesis, SQS, Lambda, API Gateway), improving cost efficiency, observability, and resilience. — Maintain infrastructure as code (Terraform) for ingestion and processing resources. — Monitor pipelines, troubleshoot, and resolve incidents. — Contribute to our ongoing work on safe data access for AI agents and tooling. — Continuously improve ingestion architecture, tooling, and engineering practices. Требования: — 5+ years of commercial Python experience in a backend or data engineering role. — Solid understanding of distributed systems architecture, including load balancing, sharding, and trade-offs between synchronous and asynchronous processing. — Hands-on experience with cloud services, preferably AWS (Lambda, API Gateway, containers in ECS/EKS). — Experience building streaming pipelines (Kinesis, SQS, or equivalents). — Experience with infrastructure as code (Terraform or equivalents). — Working knowledge of SQL: ability to read and write queries, including joins and window functions. — Commercial experience with real-world production data: ability to design systems that gracefully handle messy, duplicated, delayed, or malformed input. — Solid understanding of how data flows through production systems, including the ability to anticipate and prevent downstream issues. — Operational mindset: comfortable owning production systems and monitoring them. — Ability to make architectural decisions independently and review the work of teammates. Желательно: — Strong SQL and data modeling skills. — Experience with Snowflake and dbt. — Experience with workflow orchestrators (Airflow, Dagster, Prefect, or equivalents). — Experience working with analytics and product teams as a data provider. — Experience working with sensitive or regulated data. Условия: — Open-minded teams, a welcoming and inclusive company culture. — Competitive salary package based on expertise, skillset, and impact plus stock options. — In-office, remote and hybrid work opportunities. — Equipment needed for productivity. — Premium SIMPLE subscription. — 21 days annual leave plus bank holidays. — Flexible hours focusing on results, not desk time. О компании и ценностях: — Data-driven decision making. — Focus on impact and speed. — Ownership and responsibility. — Encouragement to push limits and innovate. — Team accountability and collaboration.

Location: Paris Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of Voodoo's gaming and consumer apps, keeping us at the forefront of the mobile industry. The team plays a key role in Voodoo's long-term strategy: it accelerates product diversification and provides a state-of-the-art growth engine to distribute and scale our games. We create solutions that drive growth with a pragmatic approach, ranging from simple search to complex machine learning systems. Within Engineering & Data, the Central Data & Analytics team makes data a reliable guide for the whole company. Data engineers, analytics engineers, data analysts and a product data PM work side by side to build and grow the foundations behind every critical business and product decision at Voodoo. This position is hybrid and requires 3 days/week in our Paris office. ROLE We’re looking for a Senior Data Engineer to join our Engineering & Data team. In this role, you’ll be responsible for a wide array of topics such as: - Build and operate robust data pipelines that keep pace with ever-evolving business needs, ensuring the architecture supports them cleanly. - Contribute to the codebase, ship and maintain your changes in production, and champion strong coding and data engineering practices. - Use AI coding tools (Claude Code, Codex, and whatever comes next) as a core part of your daily workflow — to move faster on pipelines, migrations, tests and documentation — while staying fully accountable for what you merge. - Look for opportunities to put AI inside our data platform, not just around it: LLM-assisted data quality checks, semantic layers, natural-language access to datasets, agent-driven internal tooling. - Take ownership of projects from initial discussions to release: feature estimation and scoping, architecture design, benchmarking of new technologies, product feedback. - Work in a very agile environment with a fast decision process. - Collaborate directly with back-end engineers, data scientists, mobile game and consumer app teams, product and marketing. PROFILE - Extensive experience as a Data Engineer or in a similar role. - A proven track record of building and optimizing data pipelines for massive volumes of data (at scale). - Strong experience with scalability, reliability, and security topics. - Hands-on experience coding with AI assistants and agentic tools — you know how to give them the right context, break work down for them, and review their output critically rather than trusting it blindly. - Genuine curiosity about modern tooling and practices: you follow how the data and AI ecosystem is evolving, try new tools on real problems, and form your own opinion instead of following hype. You can explain why you adopted something — or why you dropped it. - Strong analytical skills and comfort working with unstructured datasets. - Experience with Amazon Web Services. - Result-oriented and focused on the value your work creates. - Curious about business needs and keen to build innovative, pragmatic solutions that grow the business through data. - Excellent communication skills (you can speak and write English). - Experience with LLM-based systems (RAG, evals, prompt and context engineering) is a strong plus. - Experience in gaming, advertising, or another fast-growing company is a plus. - Familiarity with Voodoo's ecosystem: gaming, apps, advertising, analytics. OUR STACK - Amazon Web Services; Python; Spark; Scala; Terraform; SQL (Athena, StarRocks); DBT;; Airflow; Kubernetes; AI-assisted development tooling (Claude Code, MCP-based internal tools) BENEFITS - Competitive salary based on experience - Swile Lunch voucher - Gymlib (100% covered by Voodoo) - Premium healthcare coverage with SideCare, 100% covered for you and your family - Wellness activities in our Paris office - Remote Fridays