Senior Data Engineer (m/f/d)
Job description
Senior Data Engineer at a German HealthTech company, the first data engineer in a new data team within Product, owning the data platform that moves application, product event and business system data into Snowflake.
At a glance
- Work mode
- Remote · Germany
- Languages
- English – fluent
What you'll do
- Build and run ingestion from application databases, product events and SaaS tools into Snowflake, deciding where to buy a managed connector and where to build
- Set up orchestration with clear dependencies, retries, alerting and SLAs so failed or partial loads stop downstream work
- Design event pipelines for new products together with engineers, keeping patient data out of analytics events by design
- Maintain dbt models that connect product usage with customer, billing and revenue data
- Build data flows between HubSpot CRM and internal systems, including two-way synchronisation where needed
- Establish validation, monitoring and alerting to catch data quality problems before dashboards or board reports
- Enforce role-based access and masking in Snowflake, pseudonymisation, and deletion that propagates across raw and modelled data
- Bring code review, testing, documentation and CI/CD to data code
What we're looking for
- Several years (typically 5 or more) building production data pipelines, as a data engineer or as a backend engineer on data-intensive systems
- Strong Python: tested, maintainable production code, not only scripts
- Advanced SQL, including window functions, CTEs and query optimisation
- Production experience with Snowflake or a comparable cloud warehouse: compute sizing and cost control, role-based access, masking, and performance tuning
- Experience with dbt, or a similar tool for tested and documented transformations
- Solid ingestion fundamentals: initial versus incremental loads, change data capture from Postgres, idempotency, schema evolution, late and out-of-order data, and backfills
- Production experience with an orchestrator such as Airflow or Dagster
- Experience with AWS and with deploying your own work in containers
- A data quality mindset: profiling data, testing assumptions and building checks
- Practical knowledge of GDPR: identifying personal data and implementing pseudonymisation, access control and deletion
- Use of AI coding tools in daily work and knowing where they help and where they need checking
- Ability to own decisions as the only data engineer and to explain technical trade-offs to non-engineers
- Preference for writing over talking, resulting in clear, concise, yet complete documentation and asynchronous communications
- Fluent English, written and spoken
Nice to have
- Healthcare or regulated-domain experience (e.g. ISO 27001, C5)
- Integrating CRM and SaaS systems such as HubSpot or Salesforce, including reverse ETL or two-way sync
- Designing product event tracking (e.g. Snowplow or Segment)
- Kubernetes in production
- Reading and changing Go code
- Managing Snowflake as code
- German language skills
Your team
Data team (sits in Product)
A new data team that sits in Product, works across the company and reports to the Head of Data
Apply
About Recare Deutschland GmbH
One of the leading German HealthTech companies reshaping discharge management
Recare develops a market-leading SaaS platform and AI solutions that simplify processes in hospitals and for aftercare providers, relieve healthcare professionals, and refocus attention on patients. It connects two-thirds of all German hospitals with over 650 rehabilitation clinics and 25,000 nursing and homecare providers.
Mission
Reshape discharge management – technology-driven, patient-centered, and free from bureaucracy – and improve the healthcare system and solve administrative complexity across care journeys in Europe.
Key facts
- around 100 employees
- HealthTech
- Connects two-thirds of all German hospitals with over 650 rehabilitation clinics and 25,000 nursing and homecare providers
- Develops AI solutions alongside its SaaS platform
What they value
- Strong opinions, weakly held
- Pragmatic choice of tools and avoidance of one-size-fits-all thinking
- Bringing professionalism and empathy to how you work with others
- Strong belief in solid technical fundamentals and preference for understanding and first principles over memorization