PySpark & Databricks Data Engineer – Remote 2-3 days/wk

APG Asset Management; Heerlen; Hybrid; EUR 60,000 - 85,000; Full time

Benefits offered by this job

Hybrid work 2–3 days/week

End-of-year bonus 8.33%

Pension employer contribution

Work-from-home option

Job summary

APG Asset Management is seeking a PySpark/Databricks Developer to build and optimize data pipelines for Investment and Research Platforms. You will streamline data flows and collaborate with front office, IT, and architecture teams to translate requirements into scalable data solutions.

Ideal candidates have 5+ years in data engineering with PySpark, Databricks, and Python, plus experience with Azure Data Platform and DevOps. Hybrid work and strong English communication are valued.

Qualifications

• Strong expertise in PySpark, Databricks, and Python (OO principles).
• Experience with Azure Data Platform and DevOps practices.
• Solid background in data modeling and querying (5+ years).
• Background/degree in Computer Science / Engineering.
• Highly developed communication skills in English.
• Must be self-motivated, well organized, team player.

Responsibilities

• Develop and maintain PySpark-based data pipelines in Databricks.
• Manage Databricks workspaces, dependencies, and integrations.
• Translate business requirements into scalable data solutions.
• Collaborate with analytics teams to enhance data models for BI tools.
• Maintain Azure DevOps repositories for version control and CI/CD.
• Document solutions and share knowledge within the team.
• Engage with stakeholders including front office, IT, and architecture teams.

Skills

PySpark

Databricks

Python

Data modeling

Querying

English communication

Self-motivation

Team player

Education

Background/degree in Computer Science / Engineering

Tools

Azure Data Platform

DevOps practices

Job description

APG Asset Management is seeking a PySpark/Databricks Developer to build and optimize data pipelines for Investment and Research Platforms. You will streamline data flows and collaborate with front office, IT, and architecture teams to translate requirements into scalable data solutions.

Ideal candidates have 5+ years in data engineering with PySpark, Databricks, and Python, plus experience with Azure Data Platform and DevOps. Hybrid work and strong English communication are valued.