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Data Engineer, Python, PySpark
GROUPE LR TECHNOLOGIES. Develop data processing solutions using Python and PySpark .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing data processing solutions using Python and PySpark, with a strong focus on optimizing performance in Big Data environments and ensuring data quality throughout the pipeline lifecycle.
Highest-signal resume keywords
Python DevelopmentPySpark ExpertiseData Pipeline DevelopmentPerformance OptimizationData Quality Assurance
ATS Keywords
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Hard Skills
PythonPySparkData ProcessingBig DataDistributed ArchitecturesPerformance OptimizationData Pipeline DevelopmentTesting Best PracticesVersion ControlCode Reviews
Soft Skills
Self-DirectedDetail-OrientedTeam Collaboration
Tech Stack
Tools & technologiesPySparkPython
About the role
Key responsibilities & impact- Develop data processing solutions using Python and PySpark
- Contribute to the entire data pipeline lifecycle, from design through production deployment
- Improve processing performance in distributed environments handling large volumes of data
- Identify and resolve data quality and processing reliability issues
- Translate functional and technical requirements into suitable solutions
- Contribute to development quality through testing, code reviews, and technical documentation
- Monitor production processes and help resolve incidents
- Collaborate with Data, business, and infrastructure teams
Requirements
What you’ll need- At least 6 years of experience in development and data processing
- Strong expertise in Python and PySpark
- Familiarity with Big Data environments and distributed architectures
- Experience optimizing performance and processing large volumes of data
- Experience developing and industrializing data pipelines
- Proficiency in development best practices, including testing, version control, and code reviews
- Self-directed and detail-oriented
- Strong ability to work as part of a team