STAFIDE
Amsterdam, Netherlands
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- Recruiter Assigned giftson.p@stafide.nl
- Industry Technology
- Function Others
- Work Experience 6-8 years
- City Amsterdam
- Country Netherlands
As a Senior Data Engineer, you will:
- Design, implement, and maintain scalable data engineering solutions using PySpark in Databricks.
- Build, optimize, and support customer risk rating data pipelines on a modern cloud platform.
- Develop and maintain CI/CD pipelines to enable reliable and automated deployments.
- Integrate data platforms and external data stores through APIs.
- Optimize Delta Lake workloads using features such as MERGE, Schema Evolution, Change Data Feed (CDF), and performance optimization techniques.
- Orchestrate and monitor data workflows using Databricks Workflows and other orchestration tools where applicable.
- Troubleshoot production issues, monitor pipeline performance, and ensure data quality and platform stability.
- Collaborate closely with Business Analysts, QA Engineers, Solution Architects, and fellow Data Engineers to deliver robust, production-ready solutions.
- Mentor junior Data Engineers by sharing knowledge, reviewing solutions, and promoting engineering best practices.
What You Bring to the Table:
- 5+ years of experience in Data Engineering.
- 3+ years of hands-on experience with PySpark in enterprise-scale data platforms.
- 3+ years of experience working with Azure, AWS, or GCP.
- Experience building and maintaining CI/CD pipelines for data engineering solutions.
- Strong knowledge of Databricks and Delta Lake, including MERGE operations, Schema Evolution, Change Data Feed (CDF), and optimization techniques.
- Experience with Databricks Workflows or similar job orchestration frameworks.
- Strong understanding of Spark performance tuning, including partitioning strategies, skew handling, broadcast joins, and Spark UI analysis.
- Experience supporting production environments, monitoring data pipelines, debugging failures, and resolving performance issues.
- Proven experience delivering data products into production environments.
- Experience with Azure Data Factory.
You should possess the ability to:
- Translate complex business requirements into scalable, maintainable data engineering solutions.
- Explain technical concepts and solutions clearly to both technical and non-technical stakeholders.
- Work effectively in a dynamic environment where priorities and requirements evolve.
- Take ownership of data products throughout their lifecycle, from design through production support.
- Proactively identify opportunities for improvement and drive continuous optimization.
- Collaborate effectively with cross-functional teams, including Architects, Business Analysts, QA Engineers, Developers, and Data Engineers.
- Build highly reliable, performant, and resilient data pipelines with strong observability and monitoring.
- Mentor and guide junior engineers, enabling knowledge sharing and long-term team capability.
- Troubleshoot complex production issues and implement sustainable solutions.
What we bring to the table:
- An opportunity to build and enhance modern, cloud-based data engineering solutions using Databricks, PySpark, Azure Data Factory, and cloud technologies.
- A collaborative environment that encourages knowledge sharing, continuous learning, and technical excellence.
- Exposure to large-scale, production-grade data platforms and modern DevOps practices.
- Opportunities to work alongside experienced architects, engineers, and cross-functional teams.
- A culture that values ownership, innovation, continuous improvement, and mentoring.
- The opportunity to contribute to the successful delivery and long-term stability of a business-critical data platform.
Let’s Connect
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Giftson Paul Davidson
Phone: +31 20 369 0609 ; Extn : 151
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