Job Description

Job Description

  • Design and build scalable, cloud-native data platforms from greenfield to production
  • Implement near-real-time ingestion pipelines using event-driven patterns
  • Define and enforce platform standards, including Data Lake / Lakehouse principles, medallion architecture, and data contracts
  • Refactor and optimise existing Spark and PySpark scripts for performance and maintainability
  • Introduce best practices for code quality, testing, and CI/CD across data pipelines
  • Drive adoption of AI tooling and agentic workflows within the data engineering team
  • Ensure data quality, observability, and reliability across all pipelines and platforms
  • Develop self-service tooling and microservices to simplify platform usage for other teams

Qualifications

  • 5+ years of professional experience in Data Engineering
  • Strong Python and SQL development skills for pipeline development and optimisati...

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