Lilly is seeking a highly motivated and skilled Data Engineer to join our innovative team at Eli Lilly and Company. This role involves designing, building, and maintaining robust and scalable data pipelines and infrastructure to support our critical scientific and business initiatives, ultimately contributing to the discovery and development of life-changing medicines.

What You Will Do:

Data Engineering & Pipeline Development
• Design, develop, and optimize scalable data pipelines using Databricks, PySpark, Python, SQL, and Delta Lake to ingest, transform, and load data from diverse sources into data warehouses and data lakes.
• Build scalable, efficient Databricks pipelines implementing canonical data models across the medallion architecture (Bronze → Silver → Gold), scoped entirely within the CE trust boundary.
• Evaluate and apply Databricks capabilities and integration patterns - Unity Catalog, Delta Lake, Databricks Workflows, serverless compute, Lakebase, and ingestion connectors - selecting the right tool for each pipeline given performance, cost, and scalability constraints.
• Implement and maintain ELT/ETL workflows using Databricks Workflows, Auto Loader, Structured Streaming, and Delta Live Tables (DLT).
• Build and maintain CI/CD pipelines (GitHub Actions, Git-based promotion dev → test → prod) for CE data, contract, policy, and agent artifacts.
• Automate data ingestion and product creation to reduce manual pipeline maintenance and onboarding time for new CE data sources.

Data Governance, Quality & Security
• Implement and manage data governance policies, ensuring data quality, integrity, security, and compliance with regulatory requirements (e.g., GxP, HIPAA) and covered-entity constructs.
• Implement row/column-level security, masking, and tokenization boundaries so PHI isolation is enforced at the platform layer, in partnership with the Policy-as-Code Engineer's OPA/Rego policies.
• Support implementation of data governance capabilities including metadata management, lineage, and access control using Unity Catalog.
• Establish and implement data quality, testing, and validation methodology (pytest, DLT/Great Expectations); build monitoring and alerting to proactively catch and resolve pipeline and data issues.

Data Modeling & Architecture
• Develop and maintain data models, schemas, and metadata for efficient data storage and retrieval.
• Design data solutions following Lakehouse and Medallion Architecture (Bronze, Silver, Gold) design principles.
• Develop reusable data transformation frameworks and automated data quality checks.
• Partner with the CE Data Architect on reference architecture and patterns, providing implementation feedback that keeps designs buildable and performant at scale.
• Develop and maintain documentation for data architecture, pipelines, and processes.

Collaboration & Innovation
• Collaborate with data scientists, analysts, architects, and business stakeholders to understand data requirements and translate them into scalable technical solutions.
• Monitor data pipeline performance, troubleshoot issues, and implement solutions to ensure high availability and reliability.
• Participate in code reviews, contribute to architectural discussions, and promote best practices in data engineering.
• Evaluate and recommend new data technologies and tools to enhance the enterprise data platform capabilities.
• Support the integration of machine learning models, AI Skills, and analytical tools into production environments - ensuring PHI classification and consent travel with the data into agentic consumption paths.
• Participate in Agile ceremonies, sprint planning, and testing activities using Jira or equivalent tooling.

Your Minimum Basic Qualifications:

* At least a Bachelor's degree in Computer Science, Engineering, Information Systems, or a related quantitative field.
* 5+ years of experience in data engineering, ETL development, or a similar role.
* Proficiency in SQL and at least one programming language (e.g., Python, Java, hands-on Databricks).
* Experience with cloud data platforms (e.g., Databricks, AWS, Azure, GCP) and their associated data services (e.g., S3, Redshift, Snowflake, Azure Data Lake Storage, BigQuery).
* Proficiency with Git-based CI/CD workflows (Git Actions or equivalent) for versioned data and pipeline artifacts.

What You Should Bring:

* Excellent problem-solving skills; ability to translate architectural designs into working, tested pipelines.

* Good communication and collaboration skills - able to work effectively with architects, product owners, and multi-functional partners.

* Prior experience in the pharmaceutical or life sciences industry is preferred.

Actual compensation will depend on a candidate's education, experience, skills, and geographic location. The anticipated wage for this position is
$64,500 - $158,400

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).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly's compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

#WeAreLilly