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Senior Data Platform Engineer

Taxfix · Berlin, Germany

External listingfull-time3 months ago

About The Role

Join Taxfix, a company dedicated to simplifying tax filing for millions of users across Europe. As a Senior Data Platform Engineer, you will design, build, and operate the infrastructure and pipelines that make data reliable, compliant, and ready for AI. You will work closely with cross-functional teams and have the opportunity to contribute to meaningful, people-centric work. Enjoy a range of benefits including mental health coaching, a monthly allowance for home support services, employee stock options, and more.

  • Concevoir, construire et exploiter l'infrastructure et les pipelines qui rendent les données fiables, conformes et prêtes pour l'IA.
  • Posséder les systèmes qui déplacent les données des bases de données opérationnelles, des API et des outils SaaS vers notre environnement analytique.
  • Contribuer à l'exploitation de l'infrastructure de la plateforme cloud - gérer les ressources GCP (GCS, Dataflow, Dataproc, k8s, Pub/Sub…).
  • AI-enabled engineering practices - you actively use AI assistants and code generation tools to accelerate development and deliver, and you share effective practices with the team
  • Strong Python skills for data pipeline development - you write production code, not just scripts
  • K8S and Docker containerization - you package and deploy your own work
  • 4+ years of experience in Data Engineering or a similar role (backend engineer working on data-intensive systems counts)
  • Awareness of data privacy requirements - you can identify PII, understand GDPR, and know how to implement anonymization and deletion across multiple data layers
  • Experience with event-driven data pipelines - CQRS, event ordering, idempotency, and the difference between initial load and incremental processing
  • Infrastructure-as-code - experience with Terraform, Helm, or similar tools for provisioning and managing cloud environments
  • Data for AI readiness - you have experience preparing data for ML and AI use cases with appropriate governance, lineage, and privacy controls
  • Strong Snowflake or other modern data warehouse knowledge - resource management (compute/warehouse sizing, concurrency), security & governance (roles/RBAC, column/row-level masking), columnar storage & partitioning/clustering concepts, and query performance & cost optimization in production
  • Strong SQL skills - window functions, CTEs, query optimization are second nature
  • Expert with Airflow - you’ve built DAGs with proper task dependencies, retries, and monitoring
  • Cloud platform experience - you’ve worked with GCP (GCS, Dataflow, Dataproc etc) or equivalent AWS/Azure services and understand how to manage cloud resources at scale
  • Data quality mindset - you profile data, validate assumptions, build checks, and don’t trust that “the data looked clean”

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