Clinical Data Strategy Lead

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 our 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.

Position:  Clinical Data Strategy Lead

Detailed Description:  

At Eli Lilly and Company, 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 work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism.

The Clinical Data Strategy Lead shapes and evolves the data landscape across the clinical automation and AI program, strengthening the data foundation to manage structured and unstructured data at enterprise scale. This role builds strategic advantage through execution—driving the actual build-out of the data layer in partnership with Enterprise Data  Teams, not just creating diagrams and white papers. The ideal candidate combines strategic vision with hands-on delivery capability and deep understanding of AI-ready data architectures in regulated pharmaceutical environments.

As a data strategy lead, you will:

• Have solid hands-on expertise in front-end, back-end and cloud development along with technical leadership qualities in driving at team of experienced cloud full stack developers.
• demonstrate ability to solve a broad set of problems including highly complex ones with at least ReactJS, NodeJS, Python and AWS serverless technologies.
• perform activities such as refactoring and re-platforming and is able effectively apply DevSecOps principles best practice software architecture and development practices
• possess ability to break down moderately complex problems to implement for increased business impact
• support other team members and helps them to be successful. Actively shares learnings with team members
• drive and enforce the team process improvements, ensuring others are brought along in understanding the benefits and trade-offs
• actively promote new and innovative ideas across multiple teams and capabilities

Key Strategic Imperative: This role provides strategic edge by building a robust data foundation that augments AI strategies, moving beyond tactical approaches to establish enterprise-grade data capabilities supporting clinical automation at scale.

This role balances strategic vision with hands-on execution:

Strategic (50%)

Execution (50%)

• Define data architecture, governance frameworks, integration patterns, quality standards
• Build actual data pipelines, implement data products, deploy quality monitoring, configure integrations
• Partner with enterprise teams on enterprise strategy, align with business priorities, evangelize best practices
• Write code, configure AWS Glue/Athena, create data models, validate data quality, onboard consumers

Key Responsibilities

Data Governance & AI-Readiness (35%)

• Define and implement enterprise data quality frameworks ensuring data is AI-ready and fit-for-purpose
• Establish data quality thresholds, validation rules, and acceptance criteria for AI/ML consumption
• Standardize clinical data landscape across proprietary clinical data models
• Build automated data quality monitoring and alerting systems
• Create data lineage and metadata management frameworks for regulatory compliance
• Partner with AI/ML teams to ensure datasets meet training, validation, and production requirements
• Implement data cataloging and discovery capabilities for enterprise data assets

Data Interoperability & Integration Strategy (35%)

• Design cross-pod data integration architecture ensuring seamless data flow across clinical trial lifecycle
• Define and enforce consistent data models, schemas, and APIs across automation platforms
• Architect data integrations with upstream systems and downstream consumers
• Partner with clinical account teams to identify, standardize, and govern common data elements (CDEs)
• Align data strategies with functional priorities across biostatistics, clinical operations, regulatory affairs
• Establish API-first design principles and event-driven data exchange patterns
• Collaborate with Enterprise Data teams on enterprise data lake/warehouse strategy

Data Products Management (30%)

• Build and maintain curated inventory of standardized, reusable datasets and data products
• Create searchable data product catalog with metadata, lineage, quality scores, and consumption patterns
• Standardize data consumption patterns across clinical automation program (batch, streaming, API)
• Define data product versioning, lifecycle management, and deprecation strategies
• Establish SLAs for data product availability, freshness, quality, and performance
• Drive adoption of reusable data products to eliminate redundant data pipeline development
• Measure and optimize data product usage, performance, and business value delivery

Overarching responsibilities :

Technical Leadership

• Define and drive technical vision, architecture, and engineering standards across full-stack applications
• Lead architectural design reviews and make critical technology decisions
• Establish best practices for code quality, testing, deployment, and operations
• Evaluate and select technologies, frameworks, and tools that align with business objectives
• Champion engineering excellence through code reviews, pair programming, and technical mentorship
• Collaborate with Product and Business teams to translate requirements into scalable technical solutions
• Drive technical roadmap and balance technical debt with feature delivery

Required Qualifications:

Data Strategy & Architecture

• 10+ years in data engineering, data architecture, or data platform leadership roles
• Proven track record designing and implementing enterprise data strategies at scale
• Deep expertise in data governance frameworks, data quality management, metadata systems
• Strong understanding of AI/ML data requirements: training data, feature stores, model validation
• Experience building data product platforms and self-service data capabilities

Technical Expertise (Hands-On)

• Expert-level AWS data platform experience: S3, Glue, Athena, Lake Formation, Redshift, Kinesis
• Strong Python/PySpark skills for data pipeline development and automation
• Advanced SQL and database design across relational and NoSQL systems
• Experience with data orchestration: Apache Airflow, AWS Step Functions
• Understanding of batch and streaming data processing architectures
• Proficiency with data modeling: dimensional modeling, data vault, lake-house patterns

Leadership & Influence

• Demonstrated ability to drive strategic initiatives across matrixed organizations
• Strong vendor management: evaluating capabilities, defining SOWs, managing performance
• Excellent communication: technical depth to business stakeholder fluency
• Experience partnering with enterprise teams (data, architecture, security, compliance)
• Track record building consensus across competing priorities and stakeholder groups

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field (or equivalent experience)
• Experience in highly regulated industries (healthcare, pharma, finance)
• Proven track record working on AI/ML data platforms at scale
• Experience with data mesh, data fabric, or modern data architecture patterns
• Knowledge of data observability and quality tools
• Experience with data engineering or ML/AI integration in production systems
• Familiarity with micro-frontends, microservices or design systems
• Preferred Experience with statistical computing, clinical data, or life sciences domains

 

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.

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