Associate Director Data Engineer

MSD

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Rahway, NJWest Point, PA
Salary
$129,000–$203,100 / yr
Posted
3 days ago
Freshness
Confirmed live today
Closes
Oct 5, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $179k
This role $166k
$117k most similar roles pay here $237k

This role pays less than 57% of similar roles. Most pay $133,900–$225,000 — the shaded band above. At the midpoint, this role pays about $166k versus about $179k 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 37 open roles on FindRole.

Listed pay typically runs $117,000–$184,200 across 36 roles with salary data.

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At a glance

TL;DR · Associate Director Data Engineer

Associate Director, Data Engineer, DSCS Digital Technologies joins the Digital Insights team within the Development Sciences and Clinical Supply organization. This role focuses on building a robust data foundation to power the modeling of sterile drug product development. The successful candidate will capture, curate, and deliver experimental and process data from Sterile Product Development teams into machine learning, statistical, and hybrid modeling workflows. Key responsibilities include designing scalable data pipelines, establishing metadata schemas, automating ingestion from laboratory instruments and manufacturing systems, and developing visualization dashboards for stakeholders. Required technical skills include proficiency in Python or R using Posit, RStudio, or Jupyter environments, along with experience in ETL/ELT workflows and SQL. The role addresses the critical challenge of de-risking and optimizing sterile drug substance and product manufacturing processes across biologics and vaccines through data-driven modeling.

What you'll do

  • Build partnerships with experimentalists and engineers to gather requirements for data solutions that feed modeling pipelines.
  • Design and implement scalable data pipelines to ingest experimental and process data from sterile product development teams.
  • Translate model requirements into analysis-ready, feature-rich datasets tailored for machine learning and statistical workflows.
  • Define and enforce data standards, metadata schemas, and ontologies to ensure data interoperability.
  • Automate data ingestion from laboratory instruments, electronic lab notebooks, and manufacturing systems into cloud environments.
  • Develop data analysis and visualization workflows to surface insights from sterile product development data.
  • Create dashboards and reports for scientific and cross-functional stakeholders to support decision-making.
  • Influence the digital data strategy by identifying opportunities to improve data capture at the source.

What we're looking for

  • Ph.D. in a relevant scientific or technical field with 3 years of experience, M.S. with 5 years, or B.S. with 7 years of experience.
  • Hands-on experience in sterile drug product development and a transition into a data engineering, data science, or computational role.
  • Experience developing and deploying data pipelines, ETL/ELT workflows, and data integration solutions in a pharmaceutical context.
  • Proficiency in programming with Python and/or R using Posit, RStudio, or Jupyter.
  • Working knowledge of how data-driven models consume experimental data to deliver structured datasets for modelers.
  • Experience with one or more drug modalities such as small molecules, biologics, vaccines, peptides, or drug conjugates (preferred).
  • Familiarity with sterile CMC development workflows and laboratory data systems like ELN, LIMS, and PAT (preferred).
  • Familiarity with data-driven modeling approaches, data visualization tools, and cloud platforms like AWS (preferred).

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