Lilly is looking to lead the digital transformation of its global Quality function by enabling data-driven quality decisions, AI-enabled compliance monitoring, and shaping the data product strategy for quality assurance, control, and inspections. The goal is to build trusted and intelligent quality data products and solutions that drive real-time insights, inspection readiness, and operational excellence while meeting stringent GxP, data integrity, and compliance standards.
Requirements
- Skills in data modeling, data warehousing, data integration, data governance and an understanding of data security, data standards, and cloud architecture principles.
- Experience designing large scale data models for functional, operational, and analytical environments (Conceptual, Logical, Physical & Dimensional).
- Experience with data modelling tools like Erwin Data Modeler, ER/Studio, Lucidchart etc.
- Experience in several of the following disciplines: statistical methods, data modeling, data administration, ontology development, semantic graph construction and linked data, relational schema design.
- Demonstrated SQL/PLSQL and data modeling proficiency.
- Experience in AWS, Azure techstack and other cloud technologies.
- Experience with multiple database solutions (e.g. Postgres, Redshift, Aurora, Athena) and formal database designs (3NF, Dimensional Models).
Responsibilities
- Define, design, build, and maintain the data ingestion and integration vision, strategy, and principles for the Data, Analytics & AI (Quality).
- Develop automated data pipelines.
- 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.
- 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.
Other
- Demonstrated communication, leadership, teamwork, project delivery, and problem solving skills.
- Experienced in architectural processes (e.g. blueprinting, reference architecture, governance, etc.).
- Understanding of external data standards (e.g. HL7, CDISC, SDTM) and external data vocabularies (e.g. MedDRA, RxNorm, SNOMED).
- 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.
