Eli Lilly’s Lilly Medicine Foundry is building a data platform purpose-built for a GMP-regulated manufacturing environment. In this onsite role, you will design and deliver data pipelines and cloud data lakehouse solutions that connect IT and OT source systems across AWS and Azure, enabling reliable, scalable data products for lab, process engineering, manufacturing, quality, and analytics use cases.
Working as a Data Engineer, you will translate end-to-end understanding of how data moves through the Foundry into reusable data domains and data-as-a-product capabilities. The role emphasizes modern ingestion and extraction patterns, performance-focused implementation, and a quality mindset from the start.
What you’ll do
- Design and build data pipelines that support multiple systems across the site.
- Partner with the Data Architect and Data Scientists to understand Foundry data flows from lab systems, process engineering, and manufacturing execution to quality and process analytics, then turn those insights into reliable, scalable data products.
- Integrate IT and OT source systems with cloud data lakehouse architecture across AWS and Azure to enable analytics and AI/ML/agentic AI use cases.
- Enable the full data value chain, including capture, ingestion, integration, contextualization, harmonization, and delivery as reusable data domains and data-as-a-product.
- Apply modern patterns such as medallion architecture, streaming ingestion, and API-based extraction.
- Write clean, maintainable code and optimize for performance with careful attention to how data becomes trustworthy and analytics-ready.
- Apply GxP data integrity requirements and Good Manufacturing Practices from the beginning of design and implementation.
- Participate in design reviews, maintain traceability, and help contribute to governance frameworks that support ongoing compliance.
- Collaborate with stakeholders across Operations, Quality, Lab, and Engineering to understand data needs and elicit requirements.
- Identify gaps between operational realities and technical needs, translate them into sound designs, and communicate architecture decisions to non-technical audiences.
- Investigate upstream and downstream dependencies, seek reuse opportunities for existing services and integrations, and build in alignment with broader data architecture.
- Track emerging tools and technologies across AWS and Azure ecosystems, bring informed perspectives on adoption, and contribute to the team’s collective capability.
- Design, develop, and maintain solutions for data capture, storage, integration, and analytics in partnership with Lilly technology teams.
- Review architectures and provide practical recommendations on design patterns, performance optimization, database versions, and database deployment strategies.
- Analyze large, complex data domains and develop practical approaches for downstream data exploitation via analytics.
What you’ll bring
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related technical field.
- 5+ years of experience across several areas including data modeling, ETL/ELT, ontology development, semantic graph construction, and linked data, plus relational schema design.
- 2+ years of that experience in a relevant pharmaceutical GxP setting (CM&C, Discovery R&D, or Manufacturing).
- Experience with AWS and Azure cloud platforms.
- Experience with AI/ML/LLM concepts and tools, including building agentic AI solution sets.
- 1-3 years designing large-scale data models for functional, operational, and analytical environments (Conceptual, Logical, Physical & Dimensional).
- Demonstrated SQL and data modeling proficiency.
- Experience using data modeling tools such as ER*Studio, Erwin, or TOAD.
- Data integration experience including streaming and Industrial IoT using MQTT, AQMP, Kafka, and related protocols.
- Understanding of modern data architecture concepts, including data lakehouse and data warehousing and/or big data.
- Experience with security models and development on large data sets.
- Experience with multiple database solutions (e.g., Postgres, Redshift, Aurora, Athena, Graph DB like Neptune, NoSQL like DynamoDB and MongoDB) and formal database designs (3NF, Dimensional Models).
- Experience with Agile development, CI/CD, GitHub, and automation platforms.
- Knowledge of data functions including Data Governance, Master Data Management, and Business Intelligence.
- Prior work experience in pharma or other GMP settings.
- Solid knowledge of Computer System Validation process.
- Strong problem-solving skills for analyzing, anticipating, and resolving complex issues.
- Learning agility and curiosity, plus the ability to communicate effectively across diverse forums and methods.
Tools and technologies you may 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
Compensation and benefits
- Salary: USD 129,000 - 231,000 per year
- Company bonus (based in part on company and individual performance)
- Eligibility to participate in a company-sponsored 401(k)
- 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 (employee assistance program, fitness benefits, and employee clubs and activities)
Location
Onsite in Indianapolis, IN 46260. The role is expected to move to Lebanon, IN beginning late 2027-2028. Until then, work location remains Indianapolis.
Minimum experience: 5 years.
