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Medium: common Data Engineer role with metro location and mid-level experience increases applicant density.
Medium: core data engineering skills are transferable, but healthcare domain and compliance add moderate specificity.
High: explicit 5–8 years requirement plus mandatory Snowflake, ADF/Databricks, SQL and Python skills.
Design, develop, and maintain scalable ETL/ELT data pipelines for enterprise healthcare data platforms using Snowflake, Azure Data Factory, and Databricks.
Integrate diverse healthcare data sources (claims, membership, provider, clinical data) to support analytics, reporting, and AI/ML use cases.
Ensure data quality, governance, security, and optimize data processing performance while supporting reporting modernization and cloud-based data engineering programs.
5–8 years of experience in Data Engineering roles with enterprise-scale data pipeline and data warehouse development.
Bachelor’s degree in Computer Science, IT, Engineering, Data Science, or related field.
Hands-on experience with SQL, Python, Snowflake, Azure Data Factory, Azure Databricks, and cloud-based data engineering platforms.
Work Location: Hybrid remote in Noida, Uttar Pradesh.
Experienced in healthcare data domains including claims, membership, provider, and clinical data with knowledge of healthcare data governance and compliance.
Proven expertise in cloud data engineering, ETL/ELT frameworks, and data modeling supporting AI/ML and reporting modernization.
Skilled at collaborating with Data Architects, Data Scientists, and cross-functional teams in an Agile environment to deliver reliable, high-performance data solutions.