Data Engineer

Eli Lilly and Company

Data Engineer designing data pipelines at Lilly Medicine Foundry in Lebanon, IN. Engaging with stakeholders and ensuring data integrity and compliance standards in GxP-regulated environment.

Posted 7/29/2026full-timeLebanon • 🇺🇸 United StatesMid-LevelSenior💰 $126,000 - $224,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and building data pipelines, integrating cloud platforms like AWS and Azure, and applying AI/ML concepts to create scalable data solutions. Proficient in data modeling, ETL/ELT processes, and ensuring compliance within pharmaceutical environments.

Highest-signal resume keywords

Data Pipeline DesignCloud Platforms (AWS, Azure)AI/ML Concepts and ToolsData Modeling ProficiencyData Integration (MQTT, Kafka)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingETL/ELTSQLData GovernanceData WarehousingBig Data ConceptsAgile DevelopmentCI/CDDatabase Solutions (Postgres, Redshift, Aurora)Data Architecture

Soft Skills

Problem-Solving SkillsLearning AgilityCommunication Skills

Tools & Technologies

ER*StudioErwinTOADGitHubAutomation Platforms

Industry Keywords

Pharmaceutical GxPComputer System ValidationMaster Data ManagementBusiness IntelligenceGMP Setting

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureCloudDynamoDBETLIoTKafkaMongoDBNoSQLPostgresSQL

About the role

Key responsibilities & impact

Design and build data pipelines for the Lilly Medicine Foundry
Engage directly with business and operational collaborators to understand how data flows across the Foundry
Translate understanding into reliable, scalable data products
Integrate IT and OT source systems with cloud data Lakehouse architecture spanning AWS and Azure
Enable advanced analytics and AI/ML capabilities
Work across enterprise and edge systems, ensuring data integrity and compliance standards
Build and deliver high-quality data solutions
Engage proactively with stakeholders to understand their data needs
Invest time in understanding upstream and downstream dependencies
Participate in design reviews and contribute to governance frameworks

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Data Science, Engineering or related field
At least 3 years of experience in several of the following disciplines: statistical methods, data modeling, ETL/ELT, ontology development, semantic graph construction and linked data, relational schema design.
At least 1 year of experience in a pharmaceutical GxP or Scientific environment.
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 experience designing large scale data models for functional, operational, and analytical environments (Conceptual, Logical, Physical & Dimensional).
Demonstrated SQL and data modeling proficiency.
Experience with data modeling tools such as, ER*Studio and Erwin or TOAD.
Experience with data integration such as data streaming, Industrial IOT, using MQTT, AQMP, Kafka and related protocols.
Understanding of modern data architecture, data lakehouse, data warehousing and/or big data concepts.
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, No SQL like DynamoDB, MongoDB) and formal database designs (3NF, Dimensional Models).
Experience with Agile Development, CI/CD, Github, Automation platforms.
Demonstrated ability to analyze large, complex data domains and craft practical solutions for subsequent data exploitation via analytics.
Ability to 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.
Prior work experience working in pharma or other GMP setting.
Solid knowledge of Computer System Validation process.
Demonstrated ability to analyze, anticipate, and resolve complex issues through sound problem-solving skills.
Demonstrated learning agility and curiosity.
Desire and ability to communicate using a variety of methods in diverse forums.

Benefits

Comp & perks

Health insurance
401(k)
Pension
Vacation benefits
Medical benefits
Dental benefits
Vision benefits
Prescription drug benefits
Flexible benefits (e.g., 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 (e.g., employee assistance program, fitness benefits, and employee clubs and activities)