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Tier-1 brand, common Data Engineer title, and mid-level experience increase applicant competition.
Core data engineering skills are highly transferable across industries despite healthcare experience being beneficial.
Explicit 3+ years plus mandatory Databricks, Snowflake, and Python skills increase filter strictness.
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Design, develop, and maintain scalable ETL/ELT pipelines and enterprise data workflows primarily using Databricks, Snowflake, and Python.
Implement workflow orchestration, scheduling, dependency management, and monitor data solutions to support enterprise analytics and AI/ML initiatives.
Collaborate with analytics, AI/ML, and reporting teams while ensuring data quality, governance, security, and performance optimization across platforms.
3+ years of IT experience with a bachelor’s degree in Engineering, MCA, or MSc.
Strong experience in Databricks, Snowflake, Python programming, SQL, and data modeling.
Experience building ETL/ELT pipelines, distributed data processing, workflow orchestration, and cloud-based data engineering architectures.
Familiarity with APIs, automation frameworks, integration patterns, and exposure to Apache Spark/PySpark.
Experienced in collaborative Agile team environments with strong communication skills to work cross-functionally.
Capability to troubleshoot production issues and improve system reliability, scalability, and performance.
Comfortable contributing to AI agents, intelligent automation, modern data platforms, and innovation initiatives.