EY - GDS Consulting - AI And DATA - AWS Databricks - Senior

8 - 13 years

12 - 17 Lacs

Posted:4 days ago| Platform: Naukri logo

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Job Description

  •  Data Engineer Life Sciences R&D (Senior Level) 
  •  Experience8+ Years 
  •  Role Overview 
  • As a senior Data Engineer, you will be responsible for building robust, scalable, and compliant data pipelines from raw scientific sources to integrated and consumption-ready data products in the R&D landscape. You will partner with architects, domain SMEs, and analysts to develop re-usable components supporting early discovery, development, and regulatory needs.
  •  Key Responsibilities
  • Design and implement pipelines across L1L3 layers using Databricks and Spark.
  • Develop modular, parameterized ETL processes for large-scale scientific data integration.
  • Implement and maintain STTM mappings and transformation logic with domain BAs.
  • Build metadata-driven orchestration, logging, and observability frameworks.
  • Support performance optimization, validation, and deployment readiness across squads.
  • Collaborate with architects on cloud-native best practices and standards.
  •  Must-Have Skills
  • 8+ years of experience in data engineering, with 3+ in life sciences or R&D settings.
  • Hands-on expertise with Spark, Databricks, Delta Lake, and Python/SQL.
  • Experience in building pipelines with STTM/SDTM alignment and scientific data quality requirements.
  • Good understanding of L1L3 pipeline layering and governance controls.
  • Familiarity with GxP or other compliance-driven implementations.
  •  Nice-to-Have Skills
  • Exposure to ELNs, LIMS, compound registration systems, or bioassay platforms.
  • Knowledge of Unity Catalog, Matillion, or metadata-driven architecture approaches.
  • Experience with ingestion frameworks, schema evolution, and CI/CD for data.
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