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Strong employer brand plus mid-level data engineering skills create moderate applicant competition.
Core data engineering skills transfer across industries, though healthcare domain knowledge moderately matters.
Explicit 5–8 years requirement and mandatory Databricks, Airflow, Python and DB skills make filters strict.
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Design and implement ETL processes and data integration solutions using various database technologies including NoSQL and Relational databases.
Collaborate with cross-functional teams to translate business logic into data solutions and deliver production-ready applications in an agile environment.
Optimize and maintain ETL workflows and ensure data quality through rigorous testing and documentation.
5-8 years of relevant ETL development experience.
Hands-on experience with Python, Databricks, Airflow, and databases such as MongoDB, Postgres, Teradata, and SQL Server.
Experience with Data Warehouse, Data Lake, and Lake House technologies.
Basic Cloud experience (AWS/Azure) and DevOps skills required.
Experienced in building and optimizing enterprise-scale data integration and transformation solutions.
Comfortable working collaboratively in agile and cross-functional teams focused on delivery and technical excellence.
Possesses practical knowledge of cloud platforms with preference for candidates having AWS Developer Associate or similar certification.