Director of Data Engineering & Analytics — Hybrid Role

MSD; Ireland; Hybrid; EUR 160,000 - 210,000; Full time

Benefits offered by this job

Hybrid work arrangement

Travel 10%

Job summary

MSD is seeking a Director of Data Engineering and Analytics to lead a data engineering and analytics team across SM S&T. The role translates priorities into executable plans, delivering measurable business impact while aligning with Digital Manufacturing, MPI, IT and Global Operations.

The ideal candidate has a strong technical background in data systems and experience driving data-enabled transformation in regulated environments, with a focus on manufacturing data and process intelligence.

Qualifications

• BS in engineering, pharma sciences, data science, IT or CS with 10 years’ experience (MS 8).
• Leadership in pharmaceutical manufacturing or data science in a regulated setting.
• Deep understanding of unit operations across drug substance, drug product, packaging and analytical.

Responsibilities

• Lead data engineering initiatives to build robust data pipelines and analytics platforms.
• Translate analytics priorities into executable plans with milestones and value metrics.
• Partner with cross-functional leaders to align priorities and remove barriers to execution.
• Advance data governance and democratization of data across SM S&T and IT partners.

Skills

Advanced Analytics

Data Engineering

Process Monitoring

Strategic Alignment

Leadership

Cross-functional

Education

BS in Engineering/related

MS preferred

Tools

DataLynx

SEEQ

MPI

MES

Historians

Job description

MSD is seeking a Director of Data Engineering and Analytics to lead a data engineering and analytics team across SM S&T. The role translates priorities into executable plans, delivering measurable business impact while aligning with Digital Manufacturing, MPI, IT and Global Operations.

The ideal candidate has a strong technical background in data systems and experience driving data-enabled transformation in regulated environments, with a focus on manufacturing data and process intelligence.