Senior Manufacturing Data Engineer & Digital Integration Lead

Merck; Wilmington (DE); On-site; USD 140,000 - 190,000; Full time

Job summary

Merck is seeking a Senior Specialist in Manufacturing Data Engineering & Digital Integration to lead the design, integration, and sustainment of manufacturing data platforms across GMP operations. You will transform manufacturing, laboratory, and enterprise data into scalable data products, analytics, and AI-enabled capabilities to improve operational performance.

Responsibilities include leading cross-functional teams, architecting data integrations, and ensuring compliance with data governance

Qualifications

• Bachelor's degree in a technical field with 5+ years in data engineering, system integration, or AI/ML
• Experience leading technical teams or projects
• Proficiency in Python and SQL with exposure to R/PowerShell/JavaScript

Responsibilities

• Provide senior technical leadership for data engineering, analytics, and digital integration
• Design integrations among MES, SCADA/DCS, LIMS, ERP and cloud analytics
• Develop scalable data pipelines, APIs, and data models
• Lead end-to-end lifecycle of data products from discovery to sustainment
• Oversee validation and compliance for regulated systems

Skills

AWS

Python

SQL

SDLC

Data Integration

Data Modeling

REST APIs

Big Data

Cloud Platforms

Communication

Education

Bachelor's degree in data science/CS/engineering or related

Master's degree in Data Science/CS/Engineering (preferred)

Tools

AVEVA PI System

SEEQ

Power BI

Ignition

Tableau

Dataiku

TensorFlow/PyTorch/Scikit-learn

Azure/AWS cloud

Job description

Merck is seeking a Senior Specialist in Manufacturing Data Engineering & Digital Integration to lead the design, integration, and sustainment of manufacturing data platforms across GMP operations. You will transform manufacturing, laboratory, and enterprise data into scalable data products, analytics, and AI-enabled capabilities to improve operational performance.

Responsibilities include leading cross-functional teams, architecting data integrations, and ensuring compliance with data governance