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Tier-1 employer, mid-level generalist data role in metro with broad cloud and ETL skill requirements.
Core data engineering and cloud skills are highly transferable across industries; pharma experience only desirable.
Explicit 5–8 years preferred plus mandatory cloud, PySpark, and SQL skills create strict technical filtering.
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Operate and enhance end-to-end data pipelines and ETL jobs ensuring on-time, high-quality delivery at scale across 85+ markets.
Maintain and improve data transformation scripts using Python (Pandas, PySpark) and manage cloud data storage on AWS (S3, Redshift, EMR).
Monitor pipeline health using APIs, conduct incident investigations, implement fixes, and drive automation to reduce repeated failures.
Proficient in Python (Pandas, PySpark), SQL, Postman, and AWS services including S3, Redshift, and EMR.
Experience with data engineering, production support, or data operations; 5–8 years preferred.
Strong programming, troubleshooting, and documentation skills; ability to coordinate across teams.
Work Experience Required: 5–8 years in data engineering or related fields.
Experienced with large-scale data workflows in cloud environments and managing data flows compliant with governance requirements.
Skilled in root cause analysis and automation to improve pipeline reliability and reduce incidents.
Familiarity with pharmaceutical or healthcare data ecosystems and DevOps principles is advantageous.