Director, Data Engineering Lead Digital Insights

Job Description

DSCS Digital Technologies: Digital Insights - Director Data Engineering Lead

We are a global biopharmaceutical leader with a portfolio of prescription medicines oncology vaccines and animal health products. We are driven by our purpose to develop and deliver innovative products that save and improve lives. With 69000 employees operating in more than 140 countries we offer state of the art laboratories plants and offices that are designed to inspire our employees as we learn develop and grow in our careers. We are proud of our over 125 years of service to humanity and continue to be one of the worlds biggest investors in Research & Development.

We are seeking a Director Data Engineering Lead to join our Digital Insights (DI) team within the Development Sciences and Clinical Supply (DSCS) Digital Technologies organization (DDT). Digital is the multiplier that will allow DSCS to deliver better experiments faster efficient filing and launch more robust supply chains and higher-confidence decisions across the portfolio. The DSCS Digital Technologies organization is responsible for the invention and application of new digital tools/workflows to support scientists across drug substance development drug product development and analytical development. We aspire to embed digital technologies into the fabric of DSCS culture to drive transformational impact across the CMC this role the Director Data Engineering Lead will lead a small team of data engineers responsible for transforming complex scientific and operational data into trusted analysis-ready data products and digital workflows. This Director Data Engineering Lead will sit on the Digital Insights leadership team to set data engineering strategy and project prioritization for Digital Insights. They will partner 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 that data is structured contextualized FAIR and AI-ready.

The successful candidate will build develop and lead a high-performing data engineering team. This team will create scalable data pipelines for laboratory data harmonized data models ontologies and reusable digital assets. Responsibilities will include supporting biologics development including analytical characterization drug substance and drug product process development laboratory operations predictive sciences and emerging AI applications with subsequent expansion to other modalities. The role demands strong technical leadership organizational influence and the ability to partner closely with scientists data scientists software engineers and business stakeholders across CMC and IT thereby accelerating digital transformation.

Primary 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 Digital Insights 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.

Required Qualifications

Education

• 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.

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

Required Skills:

Preferred Skills:

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The salary range for this role is

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employees position within the salary range will be based on several 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.

We offer a comprehensive package of benefits. Available benefits include 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. More information about benefits is available at can apply for this role through (or via the Workday Jobs Hub if you are a current employee). The application deadline for this position is stated on this posting.

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