Senior Specialist, Manufacturing Data Engineering & Digital Integration

MSD

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Wilmington, DE
Salary
$117,000–$184,200 / yr
Employment
Full-time
Posted
2 days ago
Freshness
Confirmed live yesterday
Closes
Oct 16, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $180k
This role $151k
$105k most similar roles pay here $226k

This role pays less than 69% of similar roles. Most pay $146,250–$214,200 — the shaded band above. At the midpoint, this role pays about $151k versus about $180k for comparable roles.

Based on 240 similar postings.

Employer

About MSD

MSD (Merck Sharp & Dohme) is the international name for Merck & Co., a major U.S.-based pharmaceutical company.

MSD currently has 9 open roles on FindRole.

Listed pay typically runs $117,000–$184,200 across 8 roles with salary data.

Most-posted roles

View all roles at MSD

At a glance

TL;DR · Senior Specialist, Manufacturing Data Engineering & Digital Integration

The Senior Specialist, Manufacturing Data Engineering & Digital Integration serves as a senior technical leader responsible for the design, integration, and sustainment of manufacturing data platforms and connected digital solutions across GMP operations. This role involves transforming complex manufacturing, laboratory, automation, and enterprise data into scalable products, analytics, and AI-enabled capabilities to improve operational performance and decision-making. The successful candidate will build reliable data pipelines, APIs, and web services while managing systems like AVEVA PI, SEEQ, Power BI, and cloud environments. Key technical requirements include proficiency in Python and SQL, experience with REST APIs, and knowledge of machine learning frameworks such as TensorFlow or PyTorch. The role addresses the challenge of integrating OT and IT platforms within a regulated biopharmaceutical manufacturing environment to ensure data integrity and process robustness through advanced analytics and automated workflows.

What you'll do

  • Design and integrate manufacturing, laboratory, automation, and enterprise systems like MES, LIMS, and ERP into unified data platforms.
  • Develop and oversee reliable data pipelines, APIs, and web services to move information across OT and IT environments.
  • Translate complex business challenges into scalable technical strategies, solution architectures, and executable delivery plans.
  • Manage the end-to-end lifecycle of manufacturing data products from initial discovery through industrialization and ongoing sustainment.
  • Configure and administer manufacturing data platforms such as AVEVA PI System, SEEQ, and Power BI for advanced analytics.
  • Evaluate and deploy AI and machine learning solutions for predictive analytics, process monitoring, and operational efficiency.
  • Ensure all data systems comply with internal governance, cybersecurity standards, and GxP/cGMP regulatory requirements.
  • Lead validation and qualification activities for regulated computerized systems to ensure audit readiness.

What we're looking for

  • Bachelor's degree in a quantitative or technical field such as Data Science, Computer Science, Engineering, or Mathematics.
  • Minimum of five years of experience in data engineering, system integration, manufacturing systems, data analytics, or AI/ML development.
  • Demonstrated experience leading, mentoring, or directing technical contributors or complex cross-functional projects.
  • Advanced proficiency in Python and SQL with working knowledge of R, PowerShell, or JavaScript.
  • Hands-on experience with REST APIs, web services, relational databases, data modeling, and enterprise integration patterns.
  • Experience working in regulated environments using SDLC, computerized system validation, data integrity, and cybersecurity practices.
  • Master's degree in a technical field with three years of relevant experience (preferred).
  • Knowledge of biopharmaceutical manufacturing, cGMP environments, and tools like AVEVA PI System, Power BI, or cloud platforms (preferred).

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