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Data Engineer - Lilly Medicines Foundry

Job in Lebanon, Boone County, Indiana, 46052, USA
Listing for: Scorpion Therapeutics
Full Time position
Listed on 2026-02-02
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst, Data Science Manager, Data Scientist
Salary/Wage Range or Industry Benchmark: 90000 - 110000 USD Yearly USD 90000.00 110000.00 YEAR
Job Description & How to Apply Below

Role Summary

Data Engineer role focused on designing, developing, and maintaining data pipelines and data solutions for Lilly Medicines Foundry. You will integrate IT/OT systems with cloud data lakehouse architectures (AWS/Azure) to enable advanced analytics and AI/ML capabilities while ensuring data quality, integrity, and regulatory compliance. You will collaborate with business stakeholders, Data Architects, and Data Scientists to deliver data as a product and reusable data domains.

Responsibilities
  • Engage with business stakeholders to design, develop, and maintain data pipelines and data solutions that ensure availability and quality of data sets and actionable insights for the Foundry.
  • -cover data capture, integration, acquisition, contextualization, and harmonization to deliver data-as-a-product and reusable data domains and products.
  • Integrate IT/OT systems with cloud data lakehouse architecture (AWS/Azure) to enable advanced analytics and AI/ML capabilities while ensuring data integrity and regulatory compliance.
  • Collaborate closely with the Data Architect, Data Scientists, and other business and IT groups to understand enterprise infrastructure and source systems.
  • Analyze large, complex data domains and craft practical solutions for data exploitation via analytics.
  • Design, develop, and maintain data solutions for data capture, storage, integration, and analytics in partnership with Tech at Lilly teams.
  • Review and provide practical recommendations on design patterns, performance considerations, optimization, database versions, and deployment strategies.
  • Ensure data solutions adhere to regulatory requirements including FDA guidelines and GMP.
  • Demonstrate knowledge in Data Governance, Master Data Management, and Business Intelligence.
Qualifications
  • Required: Bachelor’s degree in Computer Science, Data Science, Engineering or related field
  • Required: At least 3 years of experience in statistical methods, data modeling, ETL/ELT, ontology development, semantic graph construction and linked data, relational schema design
  • Required: At least 1 year of experience in a pharmaceutical GxP or Scientific environment
  • Required: Authorized to work in the United States on a full-time basis (no sponsorship)
  • Preferred: 1-3 years of experience designing large-scale data models for functional, operational, and analytical environments (Conceptual, Logical, Physical & Dimensional)
  • Preferred: Demonstrated SQL and data modeling proficiency
  • Preferred: Experience with data modeling tools such as ER/Studio, Erwin, or TOAD
  • Preferred: Experience with cloud platforms (AWS, Azure)
  • Preferred: Experience with AI/ML/LLM concepts and building agentic AI solution sets
  • Preferred: Experience with data integration such as data streaming, Industrial IoT, MQTT, AMQP, Kafka
  • Preferred: Understanding of modern data architecture, data lakehouse, data warehousing, and/or big data concepts
  • Preferred: Experience with security models and handling large data sets
  • Preferred:

    Experience with multiple databases (Postgre

    SQL, Redshift, Aurora, Athena, Neptune, Dynamo

    DB, Mongo

    DB) and 3NF/Dimensional designs
  • Preferred: Experience with Agile, CI/CD, Git Hub, and automation platforms
  • Preferred: Prior pharma or GMP work experience
  • Preferred: Solid knowledge of Computer System Validation
  • Preferred: Strong problem-solving, learning agility, and cross-functional communication skills
Skills
  • Data modeling and SQL proficiency
  • Cloud data platforms (AWS, Azure)
  • Data governance, master data management, business intelligence
  • Experience with data integration technologies and protocols (MQTT, AMQP, Kafka)
  • Understanding of data lakehouse and data warehousing concepts
  • Regulatory awareness (FDA, GMP)
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