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Mid-level, popular Data Engineer role in a metro with broad Azure/Databricks requirements.
Core Azure/Databricks data engineering skills are transferable, though pharmaceutical domain experience adds some bias.
Mandatory 5+ years plus specific Azure, Databricks, and ETL skills increases filtering stringency.
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Provide technical leadership and support throughout the cloud-based Data Lake and Data Mesh solution lifecycle.
Develop, implement, and optimize scalable, secure big data pipelines and cloud solutions using Azure Data Factory, Azure Databricks, PySpark, and related Azure technologies.
Perform tuning and enhancement of Big Data/NoSQL environments to support high volume/velocity data streams and batch/near-real-time architectures.
5+ years experience in Database Development, Master Data Management, and Data Integration initiatives.
5+ years hands-on experience with Azure data integration technologies including Azure Data Factory, Azure Functions, Logic Apps, and Azure Databricks.
Proficient in SQL development and experienced with SDLC best practices, source control, CI/CD using Azure DevOps/GitHub.
Bachelor's degree in Computer Science, IT, Engineering, or related field preferred; Work Experience Required: 5+ years
Experienced in regulated, compliance-driven environments, preferably Pharmaceutical or Life Sciences domain knowledge.
Strong expertise in designing and supporting cloud-native data management frameworks and governance standards in Azure environments.
Familiar with Agile methodologies and tooling (Jira, Confluence), and holds relevant certifications like DP-203, DP-700, or Databricks Data Engineer Associate.