Data Engineer

Eli Lilly is hiring a Data Engineer to help the Lilly Medicine Foundry design and build data pipelines that connect IT and OT source systems to a cloud data lakehouse on AWS and Azure. This role focuses on producing reliable, scalable data products that support a GMP-regulated manufacturing environment, with an emphasis on data integrity, governance, and end-to-end data delivery.

This position is onsite at Indianapolis, IN 46260. The onsite location will transition to Lebanon, IN beginning late 2027-2028.

What you’ll do

• Design and build data pipelines that support the site’s many systems.
• Partner with the Data Architect and Data Scientists to understand how data flows across the Foundry, from lab systems and process engineering to manufacturing execution and quality, then translate that into reusable data products.
• Integrate IT and OT source systems with cloud data lakehouse architecture across AWS and Azure to enable advanced analytics and AI/ML capabilities.
• Enable the full data value chain: capture, ingestion, integration, contextualization, harmonization, and delivery as data domains and data-as-a-product.
• Apply modern engineering patterns including medallion architecture, streaming ingestion, and API-based extraction.
• Write clean, maintainable code, optimize for performance, and ensure data moves from source systems into trustworthy, analytics-ready outputs.
• Build with GxP manufacturing expectations in mind from the start, applying Quality guidelines and Good Manufacturing Practices.
• Participate in design reviews, maintain traceability, and help contribute to governance frameworks that support consistent compliance.
• Collaborate with stakeholders across Operations, Quality, Lab, and Engineering to elicit requirements and explain architectural decisions to non-technical audiences.
• Stay current on AWS and Azure data ecosystem tools, evaluate what’s worth adopting, and contribute to the team’s collective capability.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related technical field.
• 5+ years of experience in several areas such as data modeling, ETL/ELT, ontology development, semantic graph construction and linked data, and relational schema design.
• 2+ years of that data engineering experience in a relevant pharmaceutical GxP environment (CM&C, Discovery R&D, or Manufacturing).
• Experience with AWS and Azure.
• Experience with AI/ML/LLM concepts and tools, including building agentic AI solution sets.
• 1–3 years designing large-scale data models across conceptual, logical, physical, and dimensional models.
• Demonstrated SQL and data modeling proficiency.
• Experience with data modeling tools: ER*Studio, Erwin, or TOAD.
• Experience with data integration, including streaming and Industrial IoT using MQTT, AQMP, Kafka, and related protocols.
• Understanding of modern data architecture including data lakehouse and/or data warehousing and big data concepts.
• Security model experience and development on large data sets.
• Experience with multiple database solutions such as Postgres, Redshift, Aurora, Athena, Neptune, DynamoDB, and MongoDB, plus formal database design approaches (3NF, Dimensional Models).
• Experience with Agile, CI/CD, GitHub, and automation platforms.
• Knowledge of data functions including Data Governance, Master Data Management, and Business Intelligence.
• Prior experience in pharma or another GMP setting.
• Solid knowledge of Computer System Validation process.
• Demonstrated ability to analyze, anticipate, and resolve complex issues, with learning agility and curiosity.
• Ability to communicate effectively across diverse forums and modalities.

Compensation & benefits

• Salary range: USD 129,000 to 231,000 per year.
• Company bonus (depending, in part, on company and individual performance).
• 401(k) eligibility through a company-sponsored plan.
• Pension.
• Vacation benefits.
• Eligibility for medical, dental, vision, and prescription drug benefits.
• Flexible benefits (for example, healthcare and/or dependent day care flexible spending accounts).
• Life insurance and death benefits.
• Certain time off and leave of absence benefits.
• Well-being benefits such as an employee assistance program, fitness benefits, and employee clubs and activities.

Technologies you’ll work with

• AWS, Azure
• Medallion architecture, streaming ingestion, API-based extraction
• MQTT, AQMP, Kafka
• Postgres, Redshift, Aurora, Athena
• Neptune, DynamoDB, MongoDB
• SQL; ER*Studio, Erwin, TOAD
• Agile Development, CI/CD, GitHub
• GxP, GMP, Computer System Validation