Senior Data Engineer

This is a fully remote position, open to applicants in Germany.

📋 Description

• Develop and manage dependable ingestion pipelines from application databases, product events, and SaaS tools into Snowflake.

• Select between managed connectors and custom-designed ingestion solutions.

• Establish pipeline orchestration with dependencies, retries, alerts, and service level agreements (SLAs).

• Collaborate with engineers to design product event pipelines, ensuring that patient data remains excluded from analytics events.

• Maintain dbt models that link product usage with customer, billing, and revenue information.

• Create data flows between HubSpot and internal systems, including two-way synchronization as necessary.

• Implement data validation, monitoring, and alerting to prevent issues from impacting dashboards or board reports.

• Enforce role-based access, masking, pseudonymisation, and deletion propagation across both raw and modeled data in Snowflake.

• Apply standards for code review, testing, documentation, and CI/CD to data code.

• Take ownership of the data platform and influence decisions regarding architecture, tooling, orchestration, monitoring, and infrastructure-as-code.

• Collaborate across the organization with the Product data team and report directly to the Head of Data.

⛳️ Requirements

• A minimum of several years of experience, typically five or more, in building production data pipelines as a data engineer or backend engineer on data-heavy systems.

• Proficient in Python, including the development of tested and maintainable production code.

• Advanced SQL skills, encompassing window functions, CTEs, and query optimization.

• Hands-on experience with Snowflake or a similar cloud data warehouse, including compute sizing, cost management, role-based access, masking, and performance tuning.

• Familiarity with dbt or comparable tools for tested and well-documented transformations.

• Knowledge of initial versus incremental loads, change data capture from Postgres, idempotency, schema evolution, late and out-of-order data, and backfills.

• Production experience with Airflow or Dagster.

• Experience using AWS and deploying applications within containers.

• Proficient in data profiling, assumption testing, and conducting data quality checks.

• Practical understanding of GDPR regulations, including personal-data identification, pseudonymisation, access control, and deletion practices.

• Daily utilization of AI coding tools and the ability to evaluate their outputs.

• Capable of making decisions as the sole data engineer and articulating technical trade-offs to non-technical stakeholders.

• Excellent written documentation skills and effective asynchronous communication.

• Fluent in English, both written and spoken.

• Experience in healthcare or regulated domains, CRM/SaaS integrations, product event tracking, Kubernetes, Go, Snowflake-as-code, and proficiency in German are considered additional assets.

🏝️ Benefits

• Meaningful work that aids hospitals and aftercare providers through reliable data.

• Flexible working hours.

• Remote-friendly work culture.

• Possibility of workations by arrangement.

• Edenred card.

• An additional vacation day to celebrate your birthday.

• Flat organizational structure.

• A culture of mutual respect, loyalty, and recognition.