Engineer – Drug Delivery Device Development

Eli Lilly and Company • Indianapolis, IN

1d • $65,250 - $169,400 • Onsite

About The Position

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to their communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world. Organization and Position Overview: Delivery, Devices, and Connected Solutions (DDCS) sits within Eli Lilly's Product Research & Development organization. We are a diverse team of scientists and engineers responsible for discovering, designing, and developing patient-centric drug delivery solutions across a broad range of modalities — from injection devices to novel routes of administration and nanomedicines. DDCS drives the drug delivery innovation agenda across early and late development to meet the needs of an expanding portfolio that spans small molecules, biologics, and nucleic acid therapeutics. DDCS is organized around a matrix model with strong disciplinary and functional horizontals supporting innovation and commercialization verticals. Our vision is to get our medicines to more patients faster by accelerating reach and scale, guided by three strategic pillars: Delivery Systems, Robust & Sustainable, and Patient Experience + Outcomes. The Data Engineering function is a foundational horizontal capability within DDCS's Data Sciences & Digital Transformation team, responsible for building and maintaining the data infrastructure that powers scientific discovery, device innovation, and data-driven decision-making across both innovation and commercialization verticals. Data engineers partner with data scientists, AI application engineers, and scientific ML engineers throughout the DDCS matrix to ensure data pipelines, architectures, and governance frameworks are robust, compliant, and purpose-built for the unique demands of pharmaceutical device development. We are seeking a talented Data Engineer to join DDCS's data science team. This role is critical in building and maintaining robust data infrastructure that enables scientific discovery, device innovation, and data-driven decision-making across the DDCS matrix. The ideal candidate will design and implement scalable data pipelines, establish efficient data management systems, and collaborate closely with data scientists and AI engineers to accelerate insights and predictive modeling capabilities—while maintaining rigorous compliance with GxP and regulated environment standards.

Requirements

• Bachelor's degree (BS) in Computer Science, Data Science, Information Systems, Engineering, or related technical field
• 5+ years of professional experience in data engineering, software engineering, or related technical roles
• Demonstrated experience building and maintaining production data pipelines and ETL/ELT processes.
• Knowledge of data warehousing concepts and tools (e.g., Snowflake, Redshift, BigQuery).
• Cross-functional collaboration within a multidisciplinary data science organization
• Clear technical communication to both data practitioners and non-technical business partners
• Strong problem-solving and performance optimization skills
• Continuous improvement orientation and adoption of emerging data engineering standards

Nice To Haves

• Master's degree in a relevant field with 3+ years of professional experience in data engineering, software engineering, or related technical roles
• Experience in pharmaceutical, biotechnology, medical device, or healthcare industries—particularly with GxP/regulated data environments.
• Proficiency in programming languages such as Python, SQL, and/or Scala.
• Proven track record working with relational and non-relational databases.
• Experience with data pipeline orchestration tools (e.g., Apache Airflow, Prefect, Dagster).
• Experience with cloud platforms (i.e. AWS, Azure, or GCP) and their data services.
• Understanding of data modeling principles and database design.
• Cloud data architecture and platform expertise
• Data governance, compliance, and ALCOA+ adherence in regulated environments

Responsibilities

• Data Infrastructure & Pipeline Development Design, build, and maintain scalable data pipelines to support ingestion, processing, and transformation of structured and unstructured data from laboratory instruments, clinical trials, manufacturing systems, and IoT-enabled medical devices.
• Develop and optimize ETL/ELT processes to ensure data quality, consistency, and availability across DDCS horizontals and program verticals.
• Implement automated data validation, monitoring, and alerting systems to ensure pipeline reliability and data integrity.
• Create and maintain comprehensive documentation of data pipelines, workflows, and architecture decisions.
• Data Architecture & Systems Management Assess organizational data needs and conduct data flow mapping across research, development, manufacturing, and regulatory functions.
• Design and maintain data warehouses, data lakes, and data marts optimized for analytics and machine learning workloads.
• Identify, evaluate, and implement suitable data management systems and storage solutions (cloud-based and on-premises) that meet security, compliance, and scalability requirements.
• Establish and enforce data governance frameworks: data cataloging, metadata management, and access controls.
• Monitor and optimize database performance, query efficiency, and system resource utilization.
• Implement disaster recovery and business continuity plans for critical data systems.
• Cross-Functional Collaboration & Enablement Partner with data scientists and AI engineers across the DDCS matrix to understand data requirements for scientific insights, predictive modeling, and machine learning applications.
• Provide technical expertise and support to enable advanced analytics use cases in device performance optimization, patient outcomes analysis, and quality assurance.
• Translate complex technical concepts to non-technical stakeholders and gather requirements from cross-functional teams.
• Enable self-service data access through APIs, dashboards, and data visualization tools.
• Data Quality, Compliance & Governance Implement data quality frameworks and validation rules to ensure accuracy, completeness, and reliability of data assets.
• Ensure compliance with regulatory requirements (FDA 21 CFR Part 11, GxP, HIPAA) and industry standards for medical device data management.
• Maintain audit trails and ensure data traceability throughout the data lifecycle in support of ALCOA+ principles.
• Innovation & Continuous Improvement Stay current with emerging technologies and best practices in data engineering, cloud computing, and big data analytics.
• Identify opportunities to improve data infrastructure efficiency, reduce costs, and enhance capabilities.
• Contribute to the development of data engineering standards and best practices within the DDCS data science horizontal.

Benefits

• Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance).
• In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and 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; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level