Senior Data Engineer

Навыки

• Airflow
• Azure
• CI/CD
• Code review
• Data Lake
• Databricks
• Docker

О компании и продукте

• At Sytac , we build high-performing engineering teams for leading organizations. We combine a pragmatic, people-first culture with technical craftsmanship, giving engineers autonomy in real production environments. 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

Задачи

• 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

Требования

• 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
• AI-assisted development as a real part of how you work
• Strong stakeholder management — you can talk to the business and turn what they need into solid technical work
• Strong English
• NL residency required — expats already living and working in the Netherlands are very welcome
• We are not offering relocation or sponsorship for this role
• Nice to have (genuinely nice, not secretly required)
• A JVM background: Scala, Java, or Kotlin is a real plus given the software-first angle
• 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

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