Sr. Data Solutions Architect QMS

Eli Lilly - Indianapolis, IN

Full-time - Senior

Indianapolis, IN

10,001+ employees

Chemical Manufacturing

About the position

The Sr. Data Solutions Architect at Eli Lilly and Company is responsible for defining, designing, building, and maintaining the data and solution architecture vision, strategy, and principles for the Global Manufacturing and Quality teams. This role involves leading product pods focused on data, analytics, and AI, and contributing to transformation programs aimed at delivering value through durable analytic products and AI solutions.

Responsibilities

• Develop comprehensive data architectural designs and strategies for data products, durable analytic products, and AI solutions.
• Lead the design and implementation of scalable, robust, and secure data architectures to support the organization's data product portfolio.
• Provide technical leadership and guidance to cross-functional teams, ensuring adherence to best practices and architectural principles.
• Act as a solution owner, defining non-functional requirements such as alerting, monitoring, logging, etc.
• Collaborate closely with product management and business stakeholders to understand requirements and translate them into actionable technical solutions.
• Drive the end-to-end development lifecycle of data products, from ideation and design to implementation and deployment.
• Champion innovation in data product development, continuously exploring emerging technologies and methodologies to enhance product capabilities and drive business value.
• Lead large-scale transformation initiatives focused on AI and machine learning, partnering with business units to identify opportunities and define project scope.
• Design and implement AI solutions that leverage machine learning algorithms and deep learning techniques to solve complex business challenges.
• Ensure the successful integration of AI solutions into existing systems and processes, driving tangible business impact and fostering a culture of data-driven decision-making.
• Collaborate effectively with cross-functional teams, including data scientists, engineers, analysts, and business stakeholders, to deliver integrated solutions that meet business requirements.
• Serve as a trusted advisor to senior leadership, providing insights and recommendations on technology trends, industry best practices, and strategic opportunities in data and AI.
• Mentor junior resources, providing guidance and support in technical skill development and project execution.
• Collaborate with vendors and partners to leverage external expertise and technologies, ensuring alignment with organizational goals and standards.

Requirements

• 10+ years of experience in a senior-level solutions architecture role, focusing on data products and AI transformation projects.
• Strong proficiency in data architecture design, including experience with modern data platforms, cloud technologies, and big data frameworks (e.g., Hadoop, Spark, Kafka).
• 10+ years of analytics experience developing/leading data integration, data curation, and data consumption domains.
• 5+ years of hands-on experience with AI and machine learning technologies, including familiarity with common ML frameworks (e.g., TensorFlow, PyTorch) and algorithms.
• 1+ year of hands-on experience in Gen AI models (Open AI).
• Understanding of external data standards (e.g., HL7, CDISC, SDTM) and external data vocabularies (e.g., MedDRA, RxNorm, SNOMED).
• Skills in data modeling, data warehousing, data integration, data governance, and an understanding of data security, data standards, and cloud architecture principles.
• Demonstrated ability to influence IT and business strategies to drive large-scale outcomes.
• Validated skills of strong learning agility and relationship building to influence change using knowledge and relationships.
• Successful record of high quality, user-focused, on-time & budget IT service and project delivery.
• Experience with formal project management methodologies, agile frameworks (including Scrum, Kanban, SAFe, etc.) and working knowledge of associated practices and tools.
• Excellent analytical, problem-solving, and communication skills, working across agile and diverse teams.
• Experience designing large scale data models for functional, operational, and analytical environments (Conceptual, Logical, Physical & Dimensional).
• Experience with data modeling tools like Erwin Data Modeler, ER/Studio, Lucidchart, etc.
• Demonstrated SQL/PLSQL and data modeling proficiency.
• Experience in AWS, Azure tech stack, and other cloud technologies.

Nice-to-haves

• Knowledge of GxP, Pharmaceutical manufacturing processes, and automation systems.

Benefits

• Health insurance
• Dental insurance
• 401k
• Flexible scheduling
• Paid holidays
• Professional development
• Employee discount programs