Job Description

:

  • Design, develop, deploy, and operate scalable ETL and data pipelines using PySpark, Python, advanced SQL, and AWS data services
  • Own data pipeline lifecycle from requirements, mapping, development, testing, deployment, monitoring, production support, release management, and future roadmap planning
  • Build ingestion and transformation pipelines for flat files, relational databases, APIs, data warehouses, healthcare data sources, and enterprise data platforms
  • Implement mapping automation, preferably using AI, along with LLM-assisted data cleaning, transformation, data quality checks, and RAG use cases
  • Implement secure handling of PHI/PII data including encryption, access controls, auditability, retention, masking, de-identification, governance, and operational readiness

    • Knowledge, Skills, and Abilities:

  • Advanced expertise in PySpark, Python, advanced SQL, ETL best practices, data modeling, and large-scale data processing
    • ...

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