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Mid-level Data Engineer title, 5+ years, and metro location increase candidate competition.
Azure/Databricks skills transfer well, but pharma/MDM/Veeva experience raises domain specificity.
Explicit 5+ years plus mandatory Azure/Databricks/PySpark and regulated pharma experience enforce strict filters.
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Develop and maintain scalable ETL/ELT data pipelines using Azure Data Factory, Azure Databricks, and related Azure cloud technologies.
Design, implement, and support Big Data solutions including Data Lake deployment lifecycle and refining raw data for analytics presentation layers.
Collaborate across teams to implement data management, governance standards, and troubleshoot complex data/system issues in regulated environments.
5+ years of experience in Database Development, Master Data Management, and Data Integration.
Hands-on expertise with Azure Data Factory, Azure Functions, Logic Apps, Azure Databricks, and PySpark for data pipeline development.
Proficient in SQL development and optimization in Azure or relational databases.
Bachelor's degree in Computer Science, IT, Engineering, or a related field.
Experienced working in regulated, compliance-driven environments, preferably Pharmaceutical or Life Sciences domains.
Familiarity with software development life cycle (SDLC), CI/CD, and integration with Azure DevOps or GitHub.
Ability to translate business requirements into scalable cloud-based data solutions and interact with both technical and business stakeholders.
Comfortable in structured, process-driven and governance-focused organizations with experience supporting multiple clients.