Data Engineering & Analytics Leader

Merck; Rahway (NJ); Hybride; USD 142 000 - 224 000; Plein temps

Résumé du poste

Merck in Rahway, NJ seeks an Associate Director of Data Engineering and Analytics to lead complex data initiatives across SM S&T. You will partner with science, manufacturing, IT, and digital teams to boost data accessibility and drive data-driven decisions in a regulated environment.

The role requires strong technical depth, independent leadership of workstreams, and the ability to translate business needs into scalable analytics solutions. Travel to sites (<10%) is expected. Hybrid work arrangement offered.

Qualifications

• Bachelor’s degree in a technical field with eight years of experience (MS with 6).
• Experience in pharmaceutical manufacturing, technical ops, data engineering, analytics in a regulated env.
• Ability to independently lead complex workstreams across matrixed orgs.
• Strong understanding of manufacturing processes and unit operations.
• Experience designing data pipelines, analytics products, dashboards, or scalable analytics solutions.
• Strong ability to translate between technical and business stakeholders and influence without direct authority.
• Willingness to travel to manufacturing sites (<10%).

Responsabilités

• 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 remain anchored in well-defined business problems and deliver practical, scalable value.
• Serve as a credible technical partner across business, manufacturing, scientific, and digital teams.
• Convert complex processes, 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 more effectively 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 development of 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 escape delivery risks, tradeoffs, and resource constraints in a timely manner.

Connaissances

Data Engineering

Analytics

Stakeholder Influence

Regulated Environment

Matrix Organization

Communication

SQL / Databases

Python / ETL

Formation

Bachelor’s degree in Engineering / Pharma / Data Science / IT / CS

MS degree preferred

Outils

DataLynx

SEEQ

MPI

MES

Historians

Description du poste

Merck in Rahway, NJ seeks an Associate Director of Data Engineering and Analytics to lead complex data initiatives across SM S&T. You will partner with science, manufacturing, IT, and digital teams to boost data accessibility and drive data-driven decisions in a regulated environment.

The role requires strong technical depth, independent leadership of workstreams, and the ability to translate business needs into scalable analytics solutions. Travel to sites (<10%) is expected. Hybrid work arrangement offered.