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Data Engineer - Global Data Platform
IQ Staffing B.V.
About the role
Data Engineer — Azure, Databricks & Streaming
Pipelines that carry business-critical data in serious volume, both streaming and batch, and that you also happen to run. This is a data engineering role with DevOps built in: you design the lakehouse, write the PySpark and the Python tooling, ship it through CI/CD, and then own how it behaves in production. The half of the job that involves monitoring and support isn't an afterthought — it's why the pipelines stay trustworthy.
The environment
Our client is an international bank. The team builds and operates the enterprise data solutions that let the rest of the organisation exchange data in real time and in batch — reliable, secure, governed, and used by teams well outside your own.
Teams are self-managing and own their solutions end to end. The environment is heavily regulated, which shapes the engineering: governance, lineage and observability are design requirements rather than reporting overhead.
What you'll do
Design, build and maintain scalable pipelines for streaming and batch workloads.
Build and optimise processing on Databricks, Spark and Airflow.
Write Python-based data engineering solutions and automation tooling.
Design and implement lakehouse architecture on Azure.
Own the full lifecycle — development, deployment, monitoring and operational support.
Contribute to Infrastructure as Code and CI/CD practices.
Keep data quality, governance, compliance and observability standards met in practice.
Work with data architects, platform engineers, analysts and business stakeholders to deliver actual data products.
Tech stack
Core: Azure · Databricks · PySpark · Delta Lake · Airflow · Python · SQL · Azure Data Factory
Also in the mix: Kafka · Azure Data Lake Storage · Key Vault · Azure DevOps · YAML · Infrastructure as Code · Power BI
What you'll bring
Must-haves
Strong Python and SQL — both, in production.
Hands-on PySpark, Delta Lake and modern lakehouse architectures.
Pipeline orchestration with Airflow and Azure Data Factory, on Azure Databricks.
A solid grasp of streaming architectures and large-scale data processing, and of why pipelines fail at volume.
Azure services in daily use: Data Lake Storage, Key Vault, Azure DevOps.
CI/CD, Infrastructure as Code and monitoring — the DevOps half of the role.
Nice to have
Data governance, security and operational best practice in a regulated setting.
Power BI report building.
Docker, Kubernetes or wider platform engineering experience.
Azure and Databricks certifications.
You explain your design decisions well, you're comfortable being the one on the hook when a pipeline misbehaves, and you'd rather fix the cause than add another retry.
Good to know
A pre-employment screening is part of the process — standard for the financial sector.
Working language is English; Dutch is not required.
You'll need a valid EU work permit or existing right to work in the Netherlands.