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Tier-1 brand, mid-level data role in metro with broad Databricks/Python requirements increases candidate competition.
Core data engineering skills are transferable across industries, though healthcare domain experience may be preferred.
Explicit 5–8 years plus mandatory Databricks, Airflow, Python and database experience enforces strict filters.
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Design and implement ETL processes and data integration solutions using a range of database technologies and scripting languages.
Collaborate with cross-functional teams to understand data needs and deliver production-ready, efficient data workflows and applications.
Develop and document best practices to ensure quality, integrity, and supportability of large data transformation layers in an agile environment.
5-8 years of relevant ETL development and data integration experience.
Hands-on experience with NoSQL and relational databases such as MongoDB, Postgres, Teradata, and SQL Server.
Proficiency in Python scripting and experience with Databricks and Airflow for monitoring ETL workflows.
Basic cloud experience (AWS or Azure) is required; cloud certification like AWS Developer Associate is preferred but not mandatory.
Experienced in designing scalable data architecture and optimizing query performance in data warehouse, data lake, or lake house environments.
Operates effectively in agile and collaborative team settings focused on delivering complex data engineering solutions.
Comfortable with DevOps practices and continuous learning to master new technologies and improve development velocity.