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Tier-1 firm, metro location, mid-level generalist title, and broad skills create high candidate competition.
Core data engineering skills transfer well, but US healthcare domain preference increases industry specificity.
Explicit 5–8 years and mandatory Snowflake, cloud, ETL testing make screening highly selective.
Design, develop, optimize scalable backend data solutions and ETL/ELT pipelines using Snowflake, SQL, AWS/GCP, Python, Microsoft Fabric, and Azure Data Factory.
Perform end-to-end ETL testing, data validation, and defect analysis ensuring data quality and reliability for the US Healthcare domain.
Provide issue analysis, production support, and collaborate in agile delivery teams to support data integration and platform modernization initiatives.
5+ years hands-on experience in ETL testing, data warehousing, data analysis, and SQL validation.
Strong expertise in Snowflake, SQL, Unix, Snowflake performance tuning, and cloud experience with AWS/GCP including CloudWatch, Lambda, Glue, and EMR.
Working knowledge of Python, Microsoft Fabric, Azure Data Factory, and modern ETL/ELT frameworks.
Education: BE/B.Tech/ME/M.Tech/MBA/MCA with 60% or above.
Experience supporting US Healthcare data workflows and reporting requirements.
Proven ability in ownership of end-to-end ETL processes including operational dependencies and production issue resolution.
Comfortable working in an agile delivery model interfacing with engineers, QA, business analysts, and stakeholders on complex data solutions.