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Amgen Logo Amgen · IT - Software Development

Data Engineer

India, Hyderabad · Job Posted June 29, 2026
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Job Description

Let’s do this. Let’s change the world. We are looking for a talented Data Engineer, who is curious to learn and able to develop data engineering and data analytics solution in a fast-moving environment. Candidate will work closely with senior data engineer and product owner/business analyst to understand the requirement.

Job Responsibility

  • Build and operate large-scale healthcare data pipelines across batch workflows, metadata-driven ingestion, and data service publishing
  • Own end-to-end engineering from source ingestion to conformed data products, with strong focus on reliability, data quality, and operational observability
  • Partner with analytics, business, and platform teams to deliver trusted datasets for sales, claims, activity, patient, and rare disease use cases
  • Design and maintain PySpark/SQL pipelines in Databricks for landing, unified, unstitched, and published data layers
  • Build and support Airflow DAGs for scheduling, dependencies, retries, and production operations
  • Implement metadata/config-driven frameworks for ingestion, transformation, and rule-based processing
  • Develop robust data quality controls, DQ summaries, failure handling, and alerting workflows
  • Manage batch/process audit logs, run status tracking, release flags, and operational reporting
  • Integrate multi-source data (files, APIs, cloud storage, and relational systems) into governed Delta/Spark tables
  • Optimize pipeline performance using partitioning, parallelization, and query tuning
  • Collaborate on schema evolution, business-rule onboarding, and production support

Requirements

  • Bachelor's degree in Computer Science, Information Technology, or a related field with 5-9 years of relevant experience
  • Advanced Python, PySpark, and SQL (window functions, complex joins, MERGE patterns, optimization)
  • Hands-on Databricks and Airflow experience in enterprise environments
  • Experience with cloud data platforms (AWS), object storage, and secure secret handling
  • Strong data quality engineering, monitoring, and troubleshooting in regulated data contexts
  • Solid understanding of ETL orchestration, dependency management, and SLA-driven delivery
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