The Role
Design, develop, and maintain scalable PySpark/Databricks data pipelines. Build and optimize Python data processing workflows, implement orchestration (Airflow preferred), ensure data quality and performance, integrate multiple sources into analytics-ready structures, debug and enhance pipelines, and collaborate in Agile cross-functional teams.
Summary Generated by Built In
As a PySpark Data Engineer, you will:
- Design, develop, and maintain scalable data pipelines using PySpark on Databricks
- Build and optimize data processing workflows using Python
- Implement workflow orchestration and scheduling (preferably using Airflow, if applicable)
- Work in an Agile delivery environment with cross-functional teams
- Ensure data quality, performance, and reliability of data solutions
- Support integration of data from multiple sources into analytics-ready structures
What You Bring to the Table:
- 5+ years of hands-on experience in PySpark (Databricks) and Python
- Strong experience in building and maintaining data engineering pipelines
- Exposure to Airflow (preferred, not mandatory)
- 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
You should possess the ability to:
- 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
What we bring to the table:
- Opportunity to work on modern data engineering stack including Databricks and Python
- 6-month engagement duration with potential for extension based on performance
- Exposure to large-scale data engineering projects in an international environment
- Agile-driven collaborative working culture
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
LinkedIn: https://www.linkedin.com/in/giftsonpauldavidson/
Skills Required
- 5+ years of hands-on experience in PySpark (Databricks) and Python
- Strong experience building and maintaining data engineering pipelines
- Exposure to Airflow for workflow orchestration
- Overall 6-8 years of professional experience in data engineering or related roles
- Ability to develop efficient and scalable big data processing solutions using PySpark
- Debugging, optimizing, and enhancing existing data workflows and pipelines
- Strong communication skills and ability to work with distributed teams
- Good understanding of Agile development practices
- Ability to translate business requirements into technical data solutions
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The Company
What We Do
STAFIDE is a Netherlands-based niche technology talent consulting company operating across Europe. It helps organizations identify, recruit, and deploy technology professionals in areas including cybersecurity, cloud engineering, software development, data analytics, ERP, infrastructure, and digital transformation. Its services include recruitment, workforce engagement, secondment, onboarding support, workforce deployment, and workforce analytics that support technology hiring and expansion.
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