Senior Data Engineer

• We are looking for a Senior Data Engineer to join our growing Product & Tech team. In this role, you will help build and evolve our data platform, owning key pipelines and data products from end to end and contributing to the engineering decisions that shape them
• Your main goal will be to design, build, and maintain reliable data pipelines across our operational databases and analytical platform, applying quality software engineering practices to everything you ship
• You will collaborate closely with the product team and backend engineers, and work directly with business stakeholders who depend on accurate, timely data to drive product decisions
• Design, build, and maintain scalable, reliable, and well-tested data pipelines and data products
• Manage features and pipelines end-to-end: from schema design in operational databases through ingestion, transformation, and delivery of analytical datasets
• Contribute to the architecture of our data platform and help evaluate technical trade-offs with the team
• Apply and help improve standards for data modeling, data quality, testing, and code review
• Work with Product, Engineering, and business stakeholders to turn requirements into well-scoped data solutions
• Monitor, troubleshoot, and resolve pipeline incidents, and improve observability and reliability over time
• Share knowledge with the team and mentor fellow engineers through pairing and code reviews

Benefits

• 🍼 Truly flexible schedules
• 🍹 A selection of free drinks at the office
• 🎉 Regular company events
• 🎓 Mentoring and career development
• ✈️ The hotel room is your office - we allow working from another country up to 3 months a year
• 💳 Flexible compensation plan - our Edenred and become.1 cards are an open door to customisable benefits and tax savings

• Solid grasp of data modeling, including dimensional modeling and the trade-offs between operational and analytical schemas
• Strong SQL skills with PostgreSQL, including complex query design, performance tuning, indexing, and reading execution plans for both OLTP and OLAP workloads
• Proficiency in Python for data engineering, including building robust ETL/ELT pipelines and reusable modules, with strong testing and good observability
• Working knowledge of Docker and Kubernetes, including packaging and running data services and batch jobs in production
• Experience with Dagster or similar orchestrators such as Airflow, including building assets/jobs, scheduling, monitoring, and handling failures in production workflows
• Hands-on experience with dbt, building, testing, and documenting models, ideally in a layered project structure
• Experience with database schema migration tools (such as Liquibase) or data contracts
• Experience with AWS (S3, EKS, Secrets Manager)