Director, Data Engineering Lead - Digital Insights

We are a global biopharmaceutical leader with a portfolio of prescription medicines, oncology, vaccines and animal health products. Driven by our purpose to develop and deliver innovative products that save and improve lives, we employ 69,000 people across more than 140 countries. With over 125 years of service to humanity, we remain one of the world’s largest investors in Research & Development.

About the role

The Director, Data Engineering Lead will join the Digital Insights (DI) team within the Development Sciences and Clinical Supply (DSCS) Digital Technologies organization (DDT). This role leads a small team of data engineers responsible for transforming complex scientific and operational data into trusted, analysis-ready data products and digital workflows. The Director will sit on the Digital Insights leadership team to set data engineering strategy and project prioritization, partnering with DI and DDT leadership to ensure connectivity across matrixed data engineering efforts. This role serves as a critical bridge across scientific domains, digital platforms, and advanced analytics, ensuring data is structured, contextualized, FAIR, and AI-ready.

The successful candidate will build, develop, and lead a high-performing data engineering team creating scalable data pipelines for laboratory data, harmonized data models, ontologies, and reusable digital assets. The role supports biologics development, including analytical characterization, drug substance and drug product process development, laboratory operations, predictive sciences, and emerging AI applications, with expansion to other modalities.

Responsibilities

• Lead, coach, and develop a team of business-side data engineers supporting prioritized programs.
• Establish data engineering standards, development practices, and code quality expectations.
• Foster a collaborative, innovative, and customer-focused team culture.
• Manage resource allocation, prioritization, and execution across concurrent initiatives.
• Partner with the Digital Insights leadership team to define and execute the data engineering strategy aligned with DDT objectives.
• Lead the design, development, and maintenance of scalable, reliable, and reusable data pipelines.
• Drive development of domain-specific and cross-domain data products supporting analytics, visualization, modeling, and AI use cases.
• Lead implementation of data quality monitoring, lineage, metadata management, and governance practices.
• Partner with laboratory scientists, process developers, pipeline leaders, modelers, and digital product teams to understand scientific workflows and translate requirements into data solutions.
• Accelerate availability of scientific data from laboratory instruments, ELNs, manufacturing systems, and enterprise platforms.
• Enable self-service access to governed scientific data and insights.
• Support use cases involving predictive analytics, machine learning, digital twins, and agentic AI solutions.
• Partner with IT to define target-state architectures for data ingestion, transformation, storage, and consumption.
• Collaborate with enterprise IT and data governance teams to ensure alignment with corporate standards.
• Communicate technical concepts effectively to both technical and non-technical audiences.
• Influence strategic decisions through data-driven recommendations and roadmap planning.
• Help coordinate broader DDT data engineering community of practice.

Requirements

• Ph.D. in Chemical Engineering, Biochemical Engineering, Biochemistry, Engineering, Chemistry, Biology, Pharmaceutical Sciences, or a closely-related field with at least 6 years of industrial/pharmaceutical or relevant experience.
• M.S. in Chemical Engineering, Biochemical Engineering, Biochemistry, Engineering, Chemistry, Biology, Pharmaceutical Sciences, or a closely-related field with at least 8 years of industrial/pharmaceutical or relevant experience.
• B.S. in Chemical Engineering, Biochemical Engineering, Biochemistry, Engineering, Chemistry, Biology, Pharmaceutical Sciences, or a closely-related field with at least 10 years of industrial/pharmaceutical or relevant experience.
• Pharmaceutical, biotechnology, life sciences, or healthcare industry experience.
• Experience supporting laboratory, manufacturing, process development, or scientific research environments.
• Knowledge of scientific data platforms, laboratory informatics systems, and instrument-generated data.
• Experience in data engineering, software engineering, analytics engineering, or a related technical discipline.
• Demonstrated experience leading technical teams and managing scientific or enterprise data programs.
• Experience designing and deploying enterprise-scale data pipelines and data products.
• Proven success delivering complex cross-functional initiatives.
• Expertise in data engineering technologies such as Databricks, cloud data platforms, SQL, Python, and modern ETL frameworks.
• Experience with data modeling, metadata management, ontology development, and master data concepts.
• Familiarity with data lakes, lakehouses, data warehouses, and knowledge graph concepts.
• Understanding of AI/ML data requirements.

Skills

• Biological Sciences
• Biopharmaceutical Industry
• Biotechnology
• Cross-Functional Leadership
• Data Engineering
• Data Modeling
• Digital Transformation Initiatives
• Downstream Process Development
• Engineering Standards
• Laboratory Informatics
• Manufacturing Quality Control
• Manufacturing Scale-Up
• Manufacturing Systems
• Metadata Management
• Pharmaceutical Sciences
• Predictive Analytics
• Regulatory Compliance

Pay

The salary range for this role is $173,200.00 - $272,600.00. An employee’s position within the salary range will be based on factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs. The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.

Benefits

• Medical, dental, vision healthcare and other insurance benefits (for employee and family).
• Retirement benefits, including 401(k).
• Paid holidays, vacation, and compassionate and sick days.

Schedule

• 10% travel requirements.
• Hybrid flexible work arrangements.