Advisor - Scientific Data Engineer

Eli Lilly UK

Us
Base: $166,500 - $266,200; bonus/equity: compyny b...
Data harmonization and lakehouse architecture
Etl/elt pipeline development
Semantic layer and schema engineering
The AI4D team at Lilly is building an unprecedented AI foundation to advance drug discovery research by connecting scientists to petabyte-scale data through intelligent interfaces and workflows

Job Summary

  • The AI4D team at Lilly is building an unprecedented AI foundation to advance drug discovery research by connecting scientists to petabyte-scale data through intelligent interfaces and workflows.
  • As a Scientific Data Engineer, you will design and build data architectures, harmonization infrastructure, and AI-ready data products that bridge raw scientific data and AI system consumption.
  • Lilly offers a comprehensive benefits program including 401(k), pension, medical, dental, vision, flexible spending accounts, life insurance, and well-being benefits, along with an inclusive and supportive workplace culture.

Matching Summary

The AI4D team at Lilly is building an unprecedented AI foundation to advance drug discovery research by connecting scientists to petabyte-scale data through intelligent interfaces and workflows.

Salary

Base: $166,500 - $266,200; Bonus/Equity: Company bonus eligibility based on performance; Benefits: Comprehensive medical, dental, vision, 401(k), pension, life insurance, and well-being programs

Skills & Requirements

Must-have

  • Data harmonization and lakehouse architecture
  • ETL/ELT pipeline development
  • Semantic layer and schema engineering
  • AI-ready data product development
  • Proficiency in Python for data processing
  • Strong SQL skills with complex schemas
  • Experience with cloud data platforms

Nice-to-have

  • Experience with biomedical ontologies and vocabularies
  • Knowledge of data governance in regulated industries
  • Strong communication skills bridging engineers and scientists
  • Experience with knowledge graph technologies
  • Deep experience with Databricks ecosystem
  • Familiarity with biomedical or scientific data
  • Experience in pharmaceutical or biotech environments

Key Requirements

  • Bachelors degree plus 8 years data engineering experience or Masters plus 5 years
  • Experience building data pipelines for AI/ML systems
  • PhD in data or related field preferred
  • Experience with Databricks, Snowflake, or equivalent lakehouse platforms
  • Familiarity with AWS cloud data services
  • Experience in regulated industries with data governance
  • Strong SQL and Python proficiency

Work Rights

Not specified

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