Senior Data Engineer
Senior Data Engineer at Sytac building production-grade ETL/ELT pipelines in Python, PySpark, and SQL on Azure/GCP for large Dutch enterprises, treating data pipelines as software with IaC, CI/CD, Kubernetes, and Airflow.
- Compensation
- Not disclosed
- Location
- Amsterdam
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 6+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 6+ years building production software, HBO/WO level of thinking
- Expert Python and SQL across PostgreSQL, MSSQL, and Oracle
- Deep Apache Spark/PySpark for distributed processing
- Azure Databricks, Data Factory, Synapse and/or GCP BigQuery, Dataflow
- Lakehouse/Data Lake environments with Star/dimensional modelling
- Apache Airflow for orchestration
- Git, Azure DevOps Pipelines, and CI/CD for data pipelines
- Docker and Kubernetes, day to day
- Kafka for streaming, Elasticsearch where it fits
- Data quality, lineage, and governance as first-class
- AI-assisted development as a real part of workflow
- Strong stakeholder management
- Strong English, NL residency required
Nice to have
- JVM background: Scala, Java, or Kotlin
- Dutch language
- dbt, FastAPI, Terraform/Bicep
- Medallion/Delta/Iceberg/Hudi table formats
- GitHub Actions, Helm, ArgoCD
- Kafka + Debezium (CDC), Azure Event Hub/Service Bus, GCP Pub/Sub
- Snowflake, AWS Glue/Athena
- OpenAI/Azure OpenAI and LLM integration in pipelines
- MDM/reference data
Full description
Most "data engineer" roles are glorified plumbing: drag boxes around in a UI, babysit a scheduler, hope nothing breaks overnight. This is not that.
We are looking for a Senior Data Engineer who comes from software engineering and treats data pipelines like the production software they are. Version control, tests, modular design, code review. If you have ever looked at a 2,000-line notebook held together by hope and thought "this should be a properly structured repo", we should talk.
At Sytac you work inside the data platforms that run some of the Netherlands' largest companies: KLM, ABN AMRO, ING, Rabobank, Bol, Ahold. Real volume, real reliability requirements, real ownership. You join an enterprise team and ship to prod, with the autonomy to build it right instead of fast-and-sorry.
What you'll do
- Build ETL/ELT in Python, PySpark, and SQL that is as maintainable as any backend service, modular, tested, versioned. Not a pile of one-off scripts.
- Design Lakehouse environments using Medallion (Bronze/Silver/Gold) and proper dimensional/Star Schema modelling on Azure and GCP.
- Own infrastructure as code (Terraform or Bicep) and containerized deployments on Docker and Kubernetes. No clicking through portals to ship.
- Orchestrate with Apache Airflow and run real CI/CD for data (Azure DevOps/GitHub Actions) so pipelines deploy and test like applications.
- Use AI seriously in your workflow, Copilot, Cursor, Claude Code, and bring LLMs into pipelines where they earn their place, not as a buzzword.
- Translate messy business logic into clean specs, set the quality bar with the code you write, and keep lineage and governance honest.
What we're looking for
You think like a software engineer first and a data person second. Clean, tested, reusable code is your default, not an aspiration.
- 6+ years building production software, HBO/WO level of thinking.
- Expert Python and SQL across PostgreSQL, MSSQL, and Oracle.
- Deep Apache Spark/PySpark for distributed processing, plus pandas/polars for the smaller stuff.
- Azure Databricks, Data Factory, and Synapse, and/or GCP (BigQuery, Dataflow).
- Lakehouse/Data Lake environments with Star/dimensional modelling.
- Apache Airflow for orchestration.
- Git, Azure DevOps Pipelines, and CI/CD built specifically for data pipelines.
- Docker and Kubernetes, day to day.
- Kafka for streaming, Elasticsearch where it fits.
- Data quality, lineage, and governance treated as first-class, not an afterthought.