Data Engineer

Job Summary: We are seeking a highly experienced Data Engineer with strong expertise in Azure cloud technologies and Databricks. The ideal candidate will be responsible for designing, building, and optimizing scalable data pipelines and ETL processes, particularly in healthcare and pharma domains. This role requires a deep understanding of data privacy regulations and secure data handling practices. 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. Education: Bachelors Degree