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 continuously through automation, performance tuning, and proactive issue resolution.
- You communicate with clarity to technical and non-technical audiences.
Basic Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
- 8+ years of professional experience in data engineering or software engineering, including 3+ years as a tech lead, principal engineer, or senior individual contributor.
- 3+ years of hands-on experience with Reltio (or a comparable MDM platform) for profile or customer master data, including match rules, survivorship, and integration patterns.
Additional Skills & Preferences:
- Working understanding of consent and preference management (for example opt-in and opt-out, purpose, and channel), and how consent must be enforced in data pipelines and downstream use.
- Hands-on experience with Transcend (or a similar consent platform) for consent, preference, or data subject request workflows.
- Expert-level Python and PySpark, with production-grade code, automated testing, and performance tuning, and advanced SQL, including window functions, CTEs, and query optimization.
- Strong hands-on experience building data pipelines on AWS (for example S3, Glue, Lambda, Step Functions, Athena or Redshift, IAM) and Databricks, including Delta Lake.
- Experience with data modeling (dimensional and lakehouse medallion patterns) and data governance, security, and quality practices, including protection of sensitive data (PII/PHI).
- Experience with CI/CD, Git, and infrastructure-as-code (Terraform, CDK, or CloudFormation).
- Ability to lead technical design, mentor engineers, and communicate clearly with technical and non-technical stakeholders.
- Pharmaceutical, healthcare, or pharmacy industry experience, and experience in regulated environments with privacy and compliance requirements.
- Experience partnering with and influencing vendor resources on solution development and delivery.
- Experience with orchestration tools such as Apache Airflow or Databricks Workflows.
- Familiarity with data quality frameworks (for example Great Expectations or dbt tests) and with streaming platforms (Kafka, Kinesis, or MSK).
- Familiarity with data catalog and governance tools such as Unity Catalog or AWS Lake Formation.
- AWS Certified Data Engineer - Associate, AWS Solutions Architect, or Databricks Certified Data Engineer (Associate or Professional).
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).
Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is
$129,000 - $231,000Full-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
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
- 8+ years of professional experience in data engineering or software engineering.
- 3+ years of experience as a technical lead, principal engineer, or senior individual contributor.
- 3+ years of hands-on experience with Reltio or a comparable master data management platform for profile or customer master data, including match rules, survivorship, and integration patterns.
- Understanding of consent and preference management, including opt-in, opt-out, purpose, and channel enforcement.
- Hands-on experience with Transcend or a similar consent platform for consent, preference, or data subject request workflows.
- Expert-level Python and PySpark experience, including production-grade code, automated testing, and performance tuning.
- Advanced SQL experience, including window functions, common table expressions, and query optimization.
- Strong hands-on experience building data pipelines on AWS and Databricks, including Delta Lake.
- Experience with data modeling, including dimensional and lakehouse medallion patterns.
- Experience with data governance, security, quality practices, and protection of PII and PHI.
- Experience with CI/CD, Git, and infrastructure-as-code using Terraform, CDK, or CloudFormation.
- Ability to lead technical design, mentor engineers, and communicate with technical and non-technical stakeholders.
- Pharmaceutical, healthcare, or pharmacy industry experience in regulated environments with privacy and compliance requirements.
- Experience partnering with and influencing vendor resources on solution development and delivery.
- Experience with orchestration tools such as Apache Airflow or Databricks Workflows.
- Familiarity with data quality frameworks such as Great Expectations or dbt tests.
- Familiarity with streaming platforms such as Kafka, Kinesis, or MSK.
- Familiarity with data catalog and governance tools such as Unity Catalog or AWS Lake Formation.
- AWS Certified Data Engineer, AWS Solutions Architect, or Databricks Certified Data Engineer certification.
Eli Lilly and Company Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Eli Lilly and Company and has not been reviewed or approved by Eli Lilly and Company.
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Retirement Support — Feedback suggests long-term savings are bolstered by a defined-benefit pension alongside a company 401(k) match and retiree health options. These elements make total compensation feel strong beyond base salary.
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Leave & Time Off Breadth — Feedback suggests paid time off is expansive, with substantial vacation, company shutdown days, and milestone time. This breadth of leave is viewed as a meaningful part of overall rewards.
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Parental & Family Support — Feedback suggests family-building and caregiving support are robust, including paid parental leave, adoption or surrogacy assistance, and backup care. These programs enhance the perceived value of benefits across life stages.
Eli Lilly and Company Insights
What We Do
Eli Lilly and Company engages in the discovery, development, manufacture, and sale of products in pharmaceutical products business segment. For more than a century, we have stayed true to a core set of values – excellence, integrity, and respect for people – that guide us in all we do: discovering medicines that meet real needs, improving the understanding and management of disease, and giving back to communities through philanthropy and volunteerism.








