Senior Specialist, Data Engineering

MSD

Data Engineer responsible for building scalable data products and workflow automation in healthcare. Collaborating with stakeholders to drive adoption of data solutions across various operational areas.

Posted 6/23/2026full-timeRahway • California, Massachusetts, New Jersey, Pennsylvania • 🇺🇸 United StatesSenior💰 $106,200 - $167,200 per yearWebsite

Tech Stack

Tools & technologies

CloudETLPythonSQL

About the role

Key responsibilities & impact

The Data Engineer is a key member of the Discovery Operations team, responsible for independently owning the intake, prioritization, delivery, and adoption of scalable data products, workflow automations, and decision-ready insights across the Discovery, Preclinical, and Translational Medicine (DPTM) Ops portfolio — spanning capital asset life cycle management, regulatory and safety compliance, externalization, site operations, and lab support.
This role strengthens our ability to operate in an increasingly digital environment by consolidating fragmented data, building data connections across heterogeneous systems, reducing manual and repetitive work with automations, and enabling data-driven insights (including AI-assisted approaches) from interactive reporting, modeling, and simulation tools that support day-to-day decisions and review-by-exception management.
The position serves as a hands-on builder and cross-functional facilitator across the network to deliver secure, sustainable solutions aligned to organizational priorities.
This role not only delivers solutions, but also identifies demands from the labs and DPTM Ops needs, and works a governance and prioritization process to build a portfolio of projects agreed on by DPTM Ops LT.
Beyond project planning and execution, this role is vital for interfacing with business stakeholders to drive adoption through training, communication, and continuous improvements based on user feedback and metrics.
The role is also a key interface with IT groups to ensure continuity and technology advancements for current and future tools.

Requirements

What you’ll need

Minimum requirement of a bachelor's degree in computer science, data engineering, information systems, engineering, or a related quantitative discipline; equivalent experience considered.
3+ years of progressive experience in data engineering, analytics, workflow automation, or a related discipline.
Strong SQL skills and data modeling fundamentals; ability to design analytics-ready datasets that support reporting and integrated views.
Proficiency in Python for data engineering and automation (e.g., ETL/ELT, APIs, data validation, orchestration); ability to build maintainable code with tests.
Experience designing and supporting data pipelines and integrations across heterogeneous systems; familiarity with common patterns (batch, incremental loads, scheduling, monitoring).
Dashboarding and data visualization experience (Power BI preferred; comparable tools acceptable) with an emphasis on usability, performance, and governance.
Experience with cloud platforms and secure data access patterns.
Version control and documentation best practices (clear technical documentation in Confluence or similar).
Experience with Appian business orchestration development and troubleshooting.
Experience with SharePoint creation and updating.
Familiarity with agentic/AI-assisted automation approaches (e.g., LLM-enabled reporting or triage) with appropriate controls, privacy, and validation.
Experience with Microsoft Power Platform, Dataverse, or comparable low-code platforms and their integration patterns.
Experience building lightweight internal applications (e.g., Python web apps) to enable workflow automation and self-service data access.
Proven ability to translate stakeholder needs into well-scoped deliverables, manage a backlog, and communicate tradeoffs; comfortable working as a liaison with IT/support partners (e.g., AMS, platform/product teams).
Demonstrated ability to operate independently in ambiguous environments: define operating models, facilitate governance forums, and drive stakeholder alignment/adoption across multiple functions.
Change management and enablement skills: coaching users, driving adoption, and deprecating manual/spreadsheet-driven processes.
Experience in pharmaceutical, biotech, or other regulated environments.
Domain experience with operational workflows, procurement/finance reporting, equipment management, or regulated environments (e.g., GLP/GxP concepts).
Experience with Agile/Scrum delivery methodologies in a data or analytics context.
Familiarity with data cataloging, metadata management, or data governance frameworks.
Exposure to machine-learning techniques and the practical use of AI.

Benefits

Comp & perks

medical, dental, vision healthcare and other insurance benefits (for employee and family)
retirement benefits, including 401(k)
paid holidays
vacation
compassionate and sick days

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLPythonETLdata modelingdata pipelinesdata visualizationPower BIcloud platformsAppianMicrosoft Power Platform

Soft Skills

stakeholder managementcommunicationchange managementindependent operationfacilitationcoachingbacklog managementuser feedback incorporationproject planningcontinuous improvement