Data Architect

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.

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.

Data Engineering Lead

Lilly's Purpose
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 39,000 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.

Come leverage the power of data to enable the highest standards of pharmaceutical quality

The Global Data Analytics & AI Organization (DIA) is actively seeking a Data Architect for Data, Analytics & AI (Quality) to lead the digital transformation of our global Quality function. This role is critical to enabling data-driven quality decisions, AI-enabled compliance monitoring, and shaping our data product strategy for quality assurance, control, and inspections.

You will lead a team of analytics professionals, data scientists, and engineers to build trusted and intelligent quality data products and solutions. These will drive real-time insights, inspection readiness, and operational excellence while ensuring they meet stringent GxP, data integrity, and compliance standards.

This is a strategic role, pivotal to delivering high-value analytics and AI capabilities that support quality systems, inspection outcomes, compliance assurance, and patient safety.

What You'll Be Doing
You will be responsible for defining, designing, building, and maintaining the data ingestion and integration vision, strategy, and principles for the Data, Analytics & AI (Quality). You will be primarily responsible for developing automated data pipelines. You will be a key contributor to the Integration and Data Workstream with a focus on data publication strategy.

How You'll Succeed

• Partner with Lilly architects, software vendor, and third-party implementation partner to develop and execute on a technical strategy for Quality data structure and data products.
• Work with business to identify future uses for Lilly data and anticipated business results and enable processes to support these needs.
• Develop and provide expertise in enterprise data domains; this includes data relationships, data quality, understanding of business data needs and the associated technology toolsets and methodologies.

Leadership and Strategy:

• Lead and mentor a team of data engineers, fostering a culture of collaboration, innovation, and excellence.
• Define and drive the data engineering strategy, aligning with business objectives and technical requirements.
• Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and translate them into actionable engineering solutions.

Data Pipeline Development:

• Design, develop, and maintain scalable and efficient data pipelines to support data analytics, reporting, and machine learning initiatives.
• Implement best practices for data ingestion, integration, transformation, and storage, ensuring data quality, reliability, and accessibility.
• Automate data pipeline processes to improve efficiency and reduce manual intervention, leveraging tools and frameworks such as Apache Airflow, Apache Kafka, and AWS Glue.

Data Ingestion and Integration:

• Lead the development of data ingestion and integration processes, sourcing data from various internal and external sources.
• Collaborate with stakeholders to define data ingestion requirements and implement solutions for real-time and batch data integration.
• Ensure seamless data flow between systems and applications, optimizing data