Associate Director, Data Engineering and Analytics
About The Position
Within Small Molecule Science & Technology (SM S&T), this role advances digital and data capabilities to strengthen technical operations, accelerate insight generation, and improve business outcomes across the product lifecycle. The Associate Director is an individual contributor who translates data and analytics priorities into scalable solutions, sustained adoption, and measurable value. Reporting to the Director of Data Engineering and Analytics, the role leads complex data engineering and analytics initiatives across business, science, manufacturing, engineering, and digital technology. It partners across SM S&T, Digital Manufacturing Division, Digital CMC, MPI, IT, and Global Pharmaceutical Operations to improve data accessibility, analytical capability, and data-driven decision-making. The role requires technical depth, sound judgment, and the ability to independently lead workstreams, influence stakeholders, and deliver practical solutions in a regulated environment.
Requirements
- Bachelor’s degree in Engineering, Pharmaceutical Sciences, Data Science, Information Technology, Computer Science, or a related technical discipline with eight years of experience; alternatively, a master’s degree with six years of experience.
- Significant experience in pharmaceutical manufacturing, technical operations, data engineering, analytics, or related digital roles in a regulated environment.
- Demonstrated ability to independently lead complex technical workstreams and deliver results across matrixed organizations.
- Strong understanding of manufacturing processes and unit operations across Drug Substance, Drug Product, Packaging, and/or Analytical Sciences.
- Experience designing or supporting data pipelines, analytical data products, dashboards, or scalable analytics solutions.
- Ability to translate between technical and business stakeholders and influence without direct authority.
- Ability to work effectively across multiple functions, balance priorities, and manage ambiguity.
- Travel to manufacturing sites may be required, estimated at less than 10% of time.
- Skills listed include Business Decisions, Business Informatics, Business Intelligence (BI), Business Requirements Analysis, Business Workflow Analysis, Data Access, Data Aggregation, Database Administration, Data Engineering, Data Management, Data Modeling, Data Stewardship, Data Strategies, Data Visualization, Data Warehousing (DW), Delivery Management, Design Applications, Enterprise Data Management, Feature Prioritization, Implementation Methodologies, Information Management, Insight Generation, Software Development, and Software Development Life Cycle (SDLC).
Nice To Haves
- Advanced degree in a related technical discipline.
- Experience with manufacturing data and analytics platforms such as DataLynx, SEEQ, MPI, MES, historians, or similar technologies.
Responsibilities
- Lead execution of complex data engineering and analytics initiatives aligned to SM S&T priorities.
- Translate business needs into practical implementation plans, technical requirements, and measurable value outcomes.
- Independently manage high-impact workstreams, including milestones, dependencies, risks, and stakeholder alignment.
- Keep analytics efforts anchored in well-defined business problems and focused on practical, scalable value.
- Serve as a technical partner across business, manufacturing, scientific, and digital teams.
- Convert complex processes and operational and business needs into scalable analytical and data engineering solutions.
- Bridge technical and non-technical stakeholders to support alignment, clarity, and execution.
- Influence cross-functional teams where coordinated delivery is required to achieve business outcomes.
- Lead the design and enhancement of robust data pipelines, data flows, and curated datasets supporting analytics use cases.
- Improve the quality, contextualization, and accessibility of manufacturing and process data across SM S&T.
- Support scalable approaches for integrating data from source systems into analytical environments.
- Enable scientists and engineers to access and use data for process monitoring, investigations, and lifecycle management.
- Drive deployment and sustained use of analytics capabilities across Drug Substance, Drug Product, Packaging, and Analytical Sciences.
- Apply technical understanding of manufacturing and unit operations to ensure solutions are practical and fit for purpose.
- Support repeatable methods, user enablement, and working practices that improve adoption beyond centralized expertise.
- Represent technical considerations, dependencies, and value drivers in prioritization and governance discussions.
- Partner with business and digital stakeholders to clarify high-value use cases and delivery sequencing.
- Track progress, adoption, and value realization for assigned initiatives.
- Identify and escalate delivery risks, tradeoffs, and resource constraints in a timely manner.
Benefits
- Medical, dental, and vision healthcare benefits and other insurance benefits for employees and family.
- Retirement benefits, including 401(k).
- Paid holidays, vacation, compassionate days, and sick days.
- Eligible for annual bonus and long-term incentive, if applicable.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
