At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.
We are a global healthcare leader headquartered in Indianapolis, Indiana. As Technical Lead for the LillyDirect Pharmacy Covered Entity Master Data team, you will own the technical direction and delivery of the data platform that creates trusted, consented customer and partner profiles. You will set engineering standards, guide a team of data engineers, and be the go-to expert on how Reltio (profile master data) and Transcend (consent management) work with our AWS and Databricks data platform. This is a hands-on technical leadership role. Your work ensures the right data, used with the right consent, reaches patients and the business, supporting Lilly's mission to deliver life-changing medicines.
What you’ll be doing:
Master data and consent
Define and own the technical architecture for profile master data, including Reltio integration, match and merge logic, survivorship rules, and golden record delivery to downstream consumers.
Design how consent and preference data from Transcend flows through the platform, so consent status is enforced consistently in pipelines, profiles, and downstream use.
Design how data subject requests (for example access and deletion) are carried out across profile data and downstream systems, so requests are honored consistently and can be evidenced.
Partner with Privacy, Legal, Quality, and business teams to translate consent and regulatory requirements (for example HIPAA and applicable privacy laws) into technical controls.
Define technical controls for protecting sensitive data (PII/PHI), including access control, masking, encryption, and retention, in line with Lilly standards.
Build data quality, lineage, and reconciliation checks that prove profile and consent data is accurate, complete, and auditable.
Data engineering delivery
Lead design and delivery of batch and near-real-time pipelines in Python and PySpark on Databricks and AWS.
Design Delta Lake and lakehouse (medallion) structures with sound partitioning, schema evolution, and Unity Catalog governance.
Build observable pipelines with error handling, retries, alerting, and clear SLAs.
Set standards for CI/CD and infrastructure-as-code for data workloads, working with the DevOps engineer, so environments are repeatable and reviewed.
Tune SQL, Spark jobs, and data models for performance and cost.
Own production support for data pipelines, including escalation, incident response, and root cause analysis, in partnership with the DevOps engineer.
Technical leadership
Set coding standards, code review practices, and documentation (architecture decision records, runbooks, data contracts).
Mentor engineers through design reviews, pair programming, and knowledge sessions.
Partner with product owners, architects, and vendor teams to turn business needs into a clear technical roadmap, and influence vendor resources so delivery matches our data and technical direction.
Represent the team in architecture reviews, security reviews, and platform governance forums.
How You Will Succeed:
You turn business and privacy needs into technical outcomes that stakeholders understand and trust.
You set standards that others adopt, and you mentor engineers to raise the team’s technical bar.
You treat consent as a design principle, not an afterthought, and you catch risks before they reach production.
You improve systems…