Description

Key Responsibilities:

  • Design, build, and optimize robust data pipelines and ETL automation using Databricks and Azure.
  • Collaborate with data architects, DBAs, product owners, and stakeholders to align on project goals and solutions.
  • Develop scalable data pipelines in Azure using Python and Databricks for large datasets.
  • Build and optimize data lakes and backend architectures for efficient ETL processes.
  • Handle healthcare-related data (claims, pharma, PHI/PII) with strict adherence to data privacy regulations.
  • Implement security measures such as tokenization for sensitive data.
  • Leverage Azure cloud technologies to support large-scale data processing and analytics.
  • Integrate middleware solutions like MuleSoft for data processing between SAP and Databricks.
  • Drive data transformation and automation initiatives within the engineering team.


 

Required Qualifications:

  • 5+ years of experience in Databricks and ETL development.
  • Strong Azure Data Engineering background.
  • Proficiency in Azure Data Factory.
  • Experience working with PHI/PII or HIPAA-protected data.
  • Expertise in ETL automation and development.
  • Strong knowledge of Python for data engineering tasks.
  • Familiarity with healthcare or pharma-related data and compliance standards.


 

Preferred Qualifications:

  • Experience integrating middleware solutions such as MuleSoft.
  • Knowledge of SAP data processing workflows.
  • Strong collaboration and communication skills

Key Skills
Education

Any Gradute

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