Job Description

Role Type: 5-Month Contract

Location: Remote (UK-Based)

Experience Level: Lead / Senior (5+ years PySpark)

We are seeking a Lead PySpark Engineer to drive a large-scale data modernisation project, transitioning legacy data workflows into a high-performance AWS cloud environment. This is a hands-on technical role focused on converting legacy SAS code into production-ready PySpark pipelines within a complex financial services landscape.

• Code Conversion: Lead the end-to-end migration of SAS code (Base SAS, Macros, DI Studio) to PySpark using automated tools (SAS2PY) and manual refactoring.

• Pipeline Engineering: Design, build, and troubleshoot complex ETL/ELT workflows and data marts on AWS.

• Performance Tuning: Optimise Spark workloads for execution efficiency, partitioning, and cost-effectiveness.

• Quality Assurance: Implement clean coding principles, modular design, and robust unit/comparative testing to ensure data accuracy throughout the migration.

• Engineering Excellence: Maintain Git-based workflows, CI/CD integration, and comprehensive technical documentation.

• PySpark (P3): 5+ years of hands-on experience writing scalable, production-grade PySpark/Spark SQL.

• AWS Data Stack (P3): Strong proficiency in EMR, Glue, S3, Athena, and Glue Workflows.

• SAS Knowledge (P1): Solid foundation in SAS to enable the understanding and debugging of legacy logic for conversion.

• Data Modeling: Expertise in ETL/ELT, dimensions, facts, SCDs, and data mart architecture.

• Engineering Quality: Experience with parameterisation, exception handling, and modular Python design.

• Industry: Financial Services experience is highly desirable.

• Working Pattern: Fully remote with internal team collaboration days.

• Benefits: 33 days holiday entitlement (pro-rata).

Randstad Technologies is acting as an Employment Business in relation to this vacancy.