Director, Data Engineering Lead – Digital Insights

MSD

Data engineering director leading teams and scalable pipelines for a global biopharmaceutical company. Transforming laboratory and manufacturing data into governed, AI-ready scientific products.

Posted 8/12/2026full-timeRahway • Massachusetts, New Jersey, Pennsylvania • 🇺🇸 United StatesSenior💰 $173,200 - $272,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading data engineering teams and developing scalable data solutions aligned with business objectives. Proficient in managing complex data initiatives and ensuring data quality and governance across scientific and enterprise environments.

Highest-signal resume keywords

Data Engineering LeadershipEnterprise-Scale Data PipelinesDatabricks ExpertisePharmaceutical Industry ExperienceData Quality Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSoftware EngineeringAnalytics EngineeringData ModelingMetadata ManagementETL FrameworksPythonSQLAI/ML Data RequirementsCross-Functional Initiative Delivery

Soft Skills

Team LeadershipCommunication SkillsStrategic Decision InfluenceCollaboration

Tools & Technologies

DatabricksCloud Data PlatformsLaboratory Informatics SystemsScientific Data Platforms

Industry Keywords

PharmaceuticalBiotechnologyLife SciencesHealthcareScientific Research

Tech Stack

Tools & technologies

CloudETLPythonSQL

About the role

Key responsibilities & impact

Lead, coach, and develop a team of business-side data engineers
Establish data engineering standards, development practices, and code quality expectations
Manage resource allocation, prioritization, and execution across concurrent initiatives
Define and execute the Digital Insights data engineering strategy aligned with DDT objectives
Lead the design, development, and maintenance of scalable, reliable, reusable data pipelines
Drive domain-specific and cross-domain data products for analytics, visualization, modeling, and AI use cases
Implement data quality monitoring, lineage, metadata management, and governance practices
Translate scientific workflow requirements into data solutions with laboratory scientists, process developers, pipeline leaders, modelers, and digital product teams
Accelerate availability of scientific data from laboratory instruments, ELNs, manufacturing systems, and enterprise platforms
Enable self-service access to governed scientific data and insights
Support predictive analytics, machine learning, digital twins, and agentic AI use cases
Partner with IT to define target-state architectures for data ingestion, transformation, storage, and consumption
Collaborate with enterprise IT and data governance teams on corporate standards
Communicate technical concepts to technical and non-technical audiences
Influence strategic decisions through data-driven recommendations and roadmap planning
Help coordinate the broader DDT data engineering community of practice

Requirements

What you’ll need

Ph.D. in a listed scientific or engineering field plus at least 6 years of industrial/pharmaceutical or relevant experience; or M.S. plus at least 8 years; or B.S. plus at least 10 years
Experience in the pharmaceutical, biotechnology, life sciences, or healthcare industry
Experience supporting laboratory, manufacturing, process development, or scientific research environments
Knowledge of scientific data platforms, laboratory informatics systems, and instrument-generated data
Experience in data engineering, software engineering, analytics engineering, or a related technical discipline
Demonstrated experience leading technical teams and managing scientific or enterprise data programs
Experience designing and deploying enterprise-scale data pipelines and data products
Proven success delivering complex cross-functional initiatives
Expertise with Databricks, cloud data platforms, SQL, Python, and modern ETL frameworks
Experience with data modeling, metadata management, ontology development, and master data concepts
Familiarity with data lakes, lakehouses, data warehouses, and knowledge graph concepts
Understanding of AI/ML data requirements
No visa sponsorship
Relocation: Domestic
Travel requirements: 10%
Valid driving license: No

Benefits

Comp & perks

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