Associate Director, Data Engineer, DSCS Digital Technologies

MSD

. Design, build, and maintain the data foundation powering data-driven modeling of sterile drug product development .

Posted 9/21/2026full-timeUnited StatesSenior💰 $129,000 - $203,100 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing data pipelines and workflows for sterile drug product development, with proficiency in Python and R. Capable of collaborating across multidisciplinary teams to deliver data-driven solutions and influence digital data strategies.

Highest-signal resume keywords

Data Pipeline DevelopmentSterile Drug Product DevelopmentPython ProgrammingETL/ELT WorkflowsData Visualization

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ScienceMachine LearningStatistical ModelingData IntegrationData CurationFeature EngineeringData StandardsMetadata SchemasAutomated Data Ingestion

Soft Skills

Excellent CommunicationCreativityInterpersonal SkillsTeam CollaborationScientific Curiosity

Tools & Technologies

Posit/RStudioJupyterAWSDataikuDatabricksLaboratory Data SystemsData Visualization ToolsRelational DatabasesGraph DatabasesSQL

Industry Keywords

Pharmaceutical DevelopmentSterile CMC DevelopmentDrug ModalitiesRegulatory ExpectationsCross-Functional Development

Tech Stack

Tools & technologies

AWSCloudETLPythonSQL

About the role

Key responsibilities & impact

Design, build, and maintain the data foundation powering data-driven modeling of sterile drug product development
Capture, curate, and deliver experimental and process data from Sterile Product Development teams into machine learning, statistical, and hybrid modeling workflows
Partner with SPD experimentalists, process engineers, and analytical scientists to gather requirements for data solutions
Design and implement scalable data pipelines ingesting experimental and process data from SPD teams
Translate data-driven model requirements into analysis-ready, feature-rich datasets
Define and enforce data standards, metadata schemas, and ontologies
Automate data ingestion from laboratory instruments, electronic lab notebooks, PAT systems, and manufacturing systems
Integrate data with cloud-based storage and compute environments
Develop data analysis and visualization workflows
Design and build dashboards, reports, and data exports
Curate data and define requirements for automating data ingestion at scale
Influence the digital data strategy for sterile product development
Collaborate across scientific, engineering, and digital disciplines and multidisciplinary teams
Deliver scientific innovation and build trusted partnerships across stakeholder networks

Requirements

What you’ll need

Ph.D., M.S., or B.S. in Computer Science, Data Science, Engineering, Chemistry, Physics, Biology, Pharmaceutical Sciences, or a closely related field, with the corresponding required industrial/pharmaceutical or relevant experience
Ph.D. with at least 3 years of industrial/pharmaceutical or relevant experience; OR M.S. with at least 5 years; OR B.S. with at least 7 years
Hands-on experience in sterile drug product development, sterile DS and DP manufacturing processes, or closely related pharmaceutical development, with a demonstrated 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 scientific or pharmaceutical context
Proficiency programming in Python and/or R, and with Posit/RStudio/Jupyter
Working knowledge of how data-driven models consume and depend on experimental data
Excellent communication, creativity, and interpersonal skills
Proven ability to deliver complex solutions under compressed timelines in a dynamic environment
Ability to work in a team environment with cross-functional interactions
Motivation to learn new skills, willingness to take on new challenges, and scientific curiosity
US and Puerto Rico residency required
Experience with one or more drug modalities, sterile CMC development workflows, laboratory data systems, data visualization tools, AWS, Dataiku or Databricks, relational and graph databases, SQL, regulatory expectations, and cross-functional pharmaceutical development is preferred

Benefits

Comp & perks

Annual bonus
Long-term incentive, if applicable
Medical, dental, and vision healthcare
Other insurance benefits for employee and family
Retirement benefits, including 401(k)
Paid holidays
Vacation
Compassionate and sick days
Flexible work arrangements: Hybrid