Data Engineer - Medicine Foundry

As a Data Engineer based at the Lilly Medicine Foundry, you will design and build data pipelines for the site's many systems. Working closely with the Data Architect and Data Scientists, you'll engage directly with business and operational collaborators to understand how data flows across the Foundry - from lab systems, process engineering, and manufacturing execution to quality and process analytics - and translate that understanding into reliable, scalable data products.

Your core focus will be integrating IT and OT source systems with cloud data Lakehouse architecture spanning AWS and Azure, enabling the advanced analytics and AI/ML capabilities that will define how the Foundry operates. This includes the full data value chain: capture, ingestion, integration, contextualization, harmonization, and delivery as reusable data domains and data-as-a-product. You will work across enterprise and edge systems, navigate a diverse technology landscape, and ensure that everything you build meets the data integrity and compliance standards required in a GMP-regulated manufacturing environment.

• Build and deliver high-quality data solutions. : You design and develop robust data pipelines for ingestion, transformation, and integration across cloud platforms (AWS and Azure), applying modern patterns such as medallion architecture, streaming ingestion, and API-based extraction. You write clean, maintainable code, optimize for performance, and think carefully about how data flows from source systems into trustworthy, analytics-ready products.

• Ensure compliance :
  You understand the data integrity requirements of a GxP manufacturing environment and apply Quality guidelines and Good Manufacturing Practices from the start. You participate in design reviews, maintain traceability, and contribute to governance frameworks that keep the Foundry consistently compliant.

• Translate business needs into technical outcomes. You engage proactively with stakeholders across multiple modalities and business teams including Operations, Quality, Lab, and Engineering to understand their data needs. You're comfortable eliciting requirements, identifying gaps, and translating operational realities into sound technical designs — and explaining your architectural decisions back to a non-technical audience.

• Navigate a diverse enterprise landscape :
  The Foundry operates within a broader Lilly ecosystem of enterprise systems including ERP, ELN, MES, LIMS, Historians, PLM, and QMS platforms. You invest time in understanding upstream and downstream dependencies, seek opportunities to reuse existing services and integrations, and build with the broader data architecture in mind.

• Continuous learning :
  You track emerging tools and technologies across the AWS and Azure data ecosystems, bring informed perspectives on what's worth adopting, and actively contribute to the team's collective capability.

• Bring a foundational set of knowledge in: communication, leadership, teamwork, problem solving skills, solution definition, business acumen, architectural processes (e.g. blueprinting, reference architecture, governance, etc.), technical standards, project delivery, and industry knowledge.

• Staying abreast of tools and technologies to influence Technology at Lilly strategy so that it provides best usage opportunities for business

• Analyze large, complex data domains and craft practical solutions for subsequent data exploitation via analytics.

• Design, develop and maintain data solutions for data capture, storage, integration and analytics in partnership with Technology at Lilly teams.

• Review and provide practical recommendations on design patterns, performance considerations & optimization, database versions, and database deployment strategies

• Knowledgeable in data functions such as Data Governance, Master Data Management, Business Intelligence

• Bachelor’s degree in Computer Science, Data Science, Engineering or related technical field

• 5+ years of experience in several of the following disciplines: data modeling, ETL/ELT, ontology development, semantic graph construction and linked data, relational schema design.

• 2+ years of that data engineering experience should be in a relevant pharmaceutical GxP (CM&C, Discovery R&D, or Manufacturing) setting.

• Experience with cloud platforms (e.g., AWS, Azure).

• Experience with AI/ML/LLM Concepts and tools and building agentic AI solution sets

• 1-3 years of…