Advisor - Data Strategy and Orchestration - Lilly Medicine Foundry

Eli Lilly and Company•Lebanon, IN

3d•$141,000 - $224,400

About The Position

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. Organization and Position Overview: The Data Strategy & Data Orchestration Leader is a principal-level technical expert responsible for researching, designing, and implementing innovative data architectures and methodologies that position the Medicine Foundry as a leader in pharmaceutical data management. This role will develop novel approaches to data infrastructure, advance the state-of-the-art in pharmaceutical data technologies, and apply deep technical expertise to solve complex data challenges across the digital plant ecosystem. The Data Strategy & Data Orchestration Leader will pioneer modern solutions including data fabric architectures, real-time streaming platforms, ML-ready data infrastructures, and innovative data governance frameworks that balance regulatory compliance with operational agility. As a technical leader and innovator, this role collaborates as a peer expert with Tech@Lilly architects, partners with external research institutions and industry leaders, and applies specialized data architecture expertise to enable the Medicine Foundry's vision of automated, paperless, and fully integrated operations. In the Project Delivery Phase and Startup Phase of the project (2025 To 2028), roles will be fluid and dynamic as we endeavor to support the project delivery, build a new organization, develop and implement the necessary systems and business processes required to support GMP operations and build the site culture. This will require significant collaboration, creativity and resilience as the Lilly Medicines Foundry goes from design, to start-up, and to steady-state operations.

Requirements

Bachelor's, Masters or PhD in Data Science, Computer Science, Data Engineering, or related technical experience.
Years of experience required: BS - 12+ years, MS - 8+ years, PhD 2+ years in data architecture, data engineering, or related technical fields with proven track record of researching, developing, and implementing novel data solutions in complex environments.
Relevant and progressive experience in data architecture, data engineering, or related technical fields with proven track record of researching, developing, and implementing novel data solutions in complex environments.
Deep hands-on technical expertise in modern data technologies including cloud platforms (AWS, Azure, GCP), distributed systems (Spark, Dask), streaming architectures (Kafka), and advanced data integration patterns with proven ability to design and implement enterprise-scale solutions.
Research-level expertise in data architecture methodologies including data mesh, data fabric, lakehouse architectures, real-time analytics, and ML infrastructure with demonstrated history of advancing beyond industry standard practices.
Strong knowledge of pharmaceutical M&Q systems (MES, LIMS, ERP, Sample Management) and experience designing data architectures that integrate complex manufacturing and quality systems while maintaining regulatory compliance.

Nice To Haves

Experience in pharmaceutical, biotechnology, or other FDA-regulated industries with deep understanding of cGMP data integrity requirements and regulated manufacturing data environments.
Track record of technical innovation demonstrated through publications, patents, conference presentations, open-source contributions, or recognized achievements in advancing data management methodologies in pharmaceutical or life sciences domains.
Deep hands-on experience implementing pioneering data solutions such as data mesh architectures, real-time streaming analytics, knowledge graphs, feature stores, MLOps infrastructure, or data fabric platforms in production enterprise environments.
Experience with emerging data technologies including semantic data layers, graph databases, vector databases, data observability platforms, and AI-powered data management tools with ability to evaluate and implement novel approaches.
Experience working in highly matrixed pharmaceutical organizations and partnering effectively with R&D technical leaders (R5+) and IT architects to deliver innovative yet pragmatic data solutions.
Entrepreneurial mentality with demonstratedability to pioneer innovative approaches, challenge existing practices, and drive technical innovation in ambiguous, fast-paced environments requiring creativity, resilience, and high learning agility.

Responsibilities

Research, design, and implement novel data architecture approaches for pharmaceutical manufacturing that advance industry capabilities, including data mesh architectures, data fabric platforms, real-time streaming solutions, and cloud-native data services.
Develop innovative technical solutions for ML-ready data infrastructures including feature stores, MLOps platforms, model registries, experiment tracking systems, and automated ML pipeline orchestration that enable advanced analytics and AI applications.
Design and implement advanced data platforms employing modern technologies including lakehouses (Databricks, Snowflake), distributed processing (Spark, Dask), streaming architectures (Kafka, Pulsar), and cloud-native services for scalable, high-performance data infrastructure.
Collaborate with Tech@Lilly principal architects and engineers as a technical peer expert to design enterprise data architecture, evaluate emerging data technologies, and make platform decisions that balance innovation with operational requirements.
Partner with the Augmented Intelligence Leader to build technical infrastructure enabling AI/ML innovation through proper data preparation, feature engineering capabilities, model governance frameworks, and responsible AI implementation.
Develop innovative data governance frameworks and technical solutions that achieve cGMP compliance (21 CFR Part 11, EU Annex 11, ALCOA+) while enabling agility, including automated data quality monitoring, intelligent validation, and real-time audit trails.
Drive research collaborations with academic institutions, industry consortia, and technology partners to explore emerging data management methodologies and establish thought leadership that positions Medicine Foundry as a leader in pharmaceutical data innovation.
Design novel approaches to data democratization and self-service analytics in regulated environments, including semantic layers, knowledge graphs, automated metadata management, and AI-powered data discovery that enable business users while maintaining compliance.
Establish enterprise data standards, metadata frameworks, and master data management approaches that ensure seamless data flows across MES, LIMS, SAP, Sample Management, and other digital plant systems supporting the unified digital thread vision.
Lead multi-functional data governance council with PR&D, M&Q, QC, QA, and Engineering representatives to align on data requirements, quality metrics, integration approaches, and technical solutions for data integrity and regulatory compliance.
Build and mentor a high-performing team of data professionals, coaching them in advanced data technologies, innovative problem-solving approaches, and technical excellence while fostering their growth in specialized areas.

Benefits

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).

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