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Tier-1 brand, common mid-level data engineer role, and metro hiring increase applicant competition.
Healthcare data and Epic/Cerner familiarity required, reducing cross-industry transferability.
Explicit years, mandatory Azure/Databricks/Spark/SQL and healthcare domain requirements create strict filtering.
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Own the full data engineering lifecycle including design, development, deployment, and maintenance of data management solutions to support healthcare analytics.
Lead data acquisition from multiple structured and semi-structured healthcare sources to build and hydrate client data warehouses and data marts, ensuring data quality and integrity.
Collaborate with analytics teams to implement modern data frameworks, optimize data pipelines, and maintain documentation and governance for scalable, secure, and reliable data solutions.
Bachelor's degree in IT, engineering, computer science, analytics or related field is required.
Minimum 3 years of experience in Microsoft Azure Cloud, Azure Data Factory, Data Bricks, Spark/Scala/Python, ADO, and data engineering including ingestion, transformation, and storage.
Minimum 2 years of experience designing ETL/ELT solutions and managing data assets using SQL, Python, Scala, or similar languages.
Minimum 2 years of experience working with healthcare data or healthcare organizations data.
Candidate with experience creating sophisticated data frameworks for healthcare organizations and supporting data pipelines powering BI and analytics tools such as Power BI, Tableau, or MicroStrategy.
Experienced in source to target mappings, ETL design, and familiarity with Epic Clarity/Cerner Millennium data models or similar healthcare data models.
Comfortable working in cloud environments (Azure preferred) with exposure to big data storage (e.g. Amazon Redshift, Hadoop HDFS) and able to collaborate on cross-functional healthcare analytics projects.