PySpark Data Engineer (ID: 3887)
On-siteAmsterdam, North Holland, The Netherlands
Job Summary
Design, develop, and maintain scalable data pipelines using PySpark on Databricks, building and optimizing data processing workflows with Python. Implement workflow orchestration and scheduling, ensuring data quality, performance, and reliability while supporting integration of data from multiple sources into analytics-ready structures. Debug, optimize, and enhance existing data workflows within an Agile delivery environment with cross-functional teams. Translate business requirements into technical data solutions and manage multiple tasks to deliver within deadlines in a fast-paced, international setting. This 6-month engagement offers exposure to large-scale projects on a modern data engineering stack.
Required Qualifications
- 5+ years of hands-on experience in PySpark (Databricks) and Python
- Strong experience in building and maintaining data engineering pipelines
- Overall 6–8 years of professional experience in data engineering or related roles
- Strong communication skills and ability to work with distributed teams
- Good understanding of Agile development practices
- Develop efficient and scalable big data processing solutions using PySpark
- Debug, optimize, and enhance existing data workflows and pipelines
- Work independently as well as collaboratively in Agile teams
- Translate business requirements into technical data solutions
- Manage multiple tasks and deliver within deadlines in a fast-paced environment
Desired Qualifications
- Exposure to Airflow (preferred, not mandatory)
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