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Tier-1 brand, mid-level generalist data role with broad stack and metro hiring increases competition.
Core data engineering skills are transferable across industries, though healthcare domain knowledge moderately matters.
Explicit 5-8 years plus mandatory Databricks, Airflow, Python and DB skills make filters stringent.
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Design and implement ETL processes for data extraction, transformation, and loading from multiple sources.
Collaborate with cross-functional teams to understand data requirements and deliver production-ready data integration solutions.
Optimize, maintain, and ensure data integrity and quality of ETL workflows, while preparing technical documentation.
5-8 years of ETL development experience with hands-on work in data integration solutions.
Experience with NoSQL and relational databases such as MongoDB, Postgres, Teradata, SQL Server.
Proficient in Python, Databricks, Airflow monitoring, and basic cloud experience (AWS/Azure).
Work Experience Required: 5-8 years ETL development.
Experienced in designing scalable ETL pipelines supporting enterprise data architectures like Data Warehouse, Data Lake, or Lake House.
Familiar with DevOps practices and cloud environments for deployment and monitoring.
Able to engage in agile teams and accountable for delivery of complex, user-oriented data solutions.