Description

  • 5+ years of experience in Databricks and ETL development to design, build, and optimize robust data pipelines and ETL automation.
  • Collaborate effectively with data architects, DBAs, product owners, and other stakeholders to ensure alignment on project goals, requirements, and solutions.
  • Design, develop, and maintain scalable data pipelines in Azure using Python and Databricks, focusing on efficient ETL processes for large datasets.
  • Build and optimize data lakes and backend architectures, ensuring smooth data extraction, transformation, and loading (ETL) across systems.
  • Work with healthcare data (claims, pharma, PHI/PII), ensuring compliance with data privacy regulations and implementing security measures like tokenization.
  • Leverage Azure cloud technologies, particularly Databricks, to implement large-scale data processing and analytics solutions.
  • Integrate middleware solutions like MuleSoft for data processing between SAP and Databricks.
  • Drive data transformation and automation tasks, focusing on scalable and efficient solutions within the engineering team.
  • Familiarity with healthcare or pharma-related data, with expertise in handling sensitive data (PHI/PII) and implementing security measures such as tokenization

Key Skills
Education

Any Gradute

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