Engineer

Plan and run mixed-methods research — contextual inquiry, interviews, usability testing, surveys, and behavioral analytics — with scientific, clinical, safety, regulatory, and business communities to determine which data products should exist and why.

Map user journeys and data workflows across Clinical and Non-Clinical domains, surfacing friction, workarounds, and unmet needs, and analyse product telemetry alongside qualitative findings so behaviour and stated need are read together.

Translate evidence into prioritised, decision-ready requirements, data contracts, and design principles, distinguishing genuine capability gaps from usability, adoption, and change-management gaps.

Independently design, build, and own end-to-end pipelines spanning Bronze / Silver / Gold Lakehouse layers on the Databricks + AWS ecosystem, owning reliability, performance, and cost for assigned data products.

Lead the design & build of metadata-driven, reusable pipeline frameworks that reduce time-to-data, and set and enforce squad-level engineering standards and patterns.

Apply DataOps practices — automated testing, CI/CD, infrastructure-as-code (Terraform / Bicep), observability — and lead architecture and design reviews, surfacing risks and trade-offs early.

Build self-healing, AI-augmented pipelines using anomaly detection and automated remediation to reduce manual intervention and improve reliability.

Apply LLM- and agent-based tooling to accelerate pipeline development, testing, and documentation, and to automate data quality checks, schema drift detection, and lineage capture.

Use AI-assisted methods as the default for research and synthesis — study design, transcript analysis, thematic synthesis, opportunity sizing — applying rigorous human judgment to guard against over-generalised conclusions.

Deliver assigned domain data products from requirement definition through SLA-backed production operation, implementing data contracts and publishing documentation in the enterprise catalog for genuine self-service access.

Define and track experience measures (task success, time to insight, trust in data, adoption) and establish baselines that make improvement visible over time.

Shape how enterprise platforms and third-party solutions are evaluated, selected, and configured — user-centred criteria, proofs of concept, fit-gap analysis, and evidence-based build / buy / configure recommendations supported by working prototypes.

Advance Lilly's federated data mesh model by applying domain data-ownership and governance patterns within assigned products.

Mentor engineers through code review, pairing, and practical guidance, and establish the quality bar for how user evidence is gathered, interpreted, and reflected in build decisions.

Package proven engineering patterns, research methods, and accelerators as reusable components for adoption across Clinical and Non-Clinical squads.

Build effective relationships with clinical data managers, biostatisticians, product owners, and solution architects, communicating technical trade-offs, findings, and delivery status to technical and non-technical audiences alike.

Maintain alignment between business strategy and the technology landscape over time, supporting standards-compliant pipelines that accelerate availability of clinical trial data for regulatory submission.

Data mesh and data product architecture principles; API-first data design; data marketplace, catalog, and self-service analytics adoption.

GxP / 21 CFR Part 11 compliance in a validated data environment.

MLOps / feature store integration supporting AI/ML model development.

Real-world evidence (RWE) or patient-generated data pipeline experience.

At Lilly, caring is not only what we do for patients. It is how we work. We believe the people who dedicate themselves to making medicines better deserve an environment that makes their lives better too, one where they are supported, respected, and given the space to do their best work. This is not just a policy. It is who we are.

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 an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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 does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.