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Tier-1 employer, metro location, and broad Databricks/AWS skillset create high competition.
Strong Databricks/Delta Lake, regulated GxP/HIPAA, and pharma domain needs make background fit highly sensitive.
Explicit 12+ years, mandatory Databricks/AWS expertise, and GxP/HIPAA compliance raise shortlisting strictness to high.
Lead design, architecture, and implementation of enterprise-scale data platforms using Databricks, AWS, PySpark, Delta Lake, and modern DataOps practices.
Define and govern enterprise data engineering standards and reusable frameworks to build scalable, secure, and compliant data solutions across R&D, Clinical, Regulatory, Commercial, and Enterprise Analytics domains.
Provide technical leadership, mentor engineering teams, and collaborate cross-functionally to ensure data platform excellence, quality, and regulatory compliance.
Bachelor's or master's degree in Computer Science, Engineering, Information Systems, or related field.
12+ years of experience in Data Engineering, Big Data, Data Platforms, or Cloud Engineering.
4-5 years of experience architecting enterprise-scale data solutions on Databricks and AWS.
Expertise required in Databricks, Delta Lake, Unity Catalog, Spark, PySpark, SQL, advanced Python, AWS services, CI/CD practices, Infrastructure as Code (Terraform, CloudFormation, or AWS CDK).
Senior technical leader with deep expertise in modern cloud data platforms, distributed processing, and software engineering best practices.
Experienced in leading architecture and data platform modernization in regulated environments, ideally with Life Sciences or healthcare data domain exposure.
Able to drive cross-functional collaboration and establish standards that accelerate reliable data product delivery and operational excellence.