Associate Director, Data Engineering and Analytics

MSD•Upper Gwynedd Township, PA

1d•$142,400 - $224,100•Hybrid

About The Position

Within Small Molecule Science & Technology (SM S&T), the Associate Director, Data Engineering and Analytics will translate data and analytics priorities into scalable solutions, sustained adoption, and measurable value. This is a critical individual-contributor role leading complex data engineering and analytics initiatives at the intersection of business, science, manufacturing, engineering, and digital technology. Reporting to the Director of Data Engineering and Analytics, the role serves as a trusted technical partner across a highly matrixed environment, including SM S&T, Digital Manufacturing Division, Digital CMC, MPI, IT, and Global Pharmaceutical Operations. The position requires technical depth, sound judgment, and the ability to independently lead workstreams, influence stakeholders, and deliver practical solutions in a regulated environment. The role advances data accessibility, analytical capability, and data-driven decision-making across the product lifecycle. It supports data pipeline and analytical solution design, improves manufacturing and process data quality and accessibility, and helps scientists and engineers use data for process monitoring, investigations, and lifecycle management. The position is hybrid, based primarily in Rahway, New Jersey, and may require travel to manufacturing sites, estimated at less than 10% of the time.

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.
Strong ability to translate between technical and business stakeholders and influence without direct authority.
Demonstrated 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 the time.

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.
Ensure analytics efforts address well-defined business problems and deliver practical, scalable value.
Serve as a technical partner across business, manufacturing, scientific, and digital teams.
Convert complex processes, operational needs, 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 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.