Director R&D Data Systems

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and Med Tech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn

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Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Engineering

Job Category:

People Leader

All Job Posting Locations:

Raritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

We are searching for the best talent for a Director, R&D Data Systems to be located in Titusville, NJ, Spring House, PA or Raritan, NJ.

The Director, Cross R&D Data Systems, Innovative Medicines is responsible for leading shared data technology capabilities that enable trusted, governed, discoverable, interoperable, and reusable data across the Innovative Medicine R&D ecosystem. The role ensures that data platforms, quality controls, cataloging, master data, ingestion, transformation, and cross-functional data products are operated as enterprise-grade capabilities that support analytics, AI, GenAI, regulatory, safety, discovery, development, and operational use cases.

This role partners across data product teams, analytics/model teams, functional data owners, and business stakeholders to run an integrated Data & AI operating model. The role translates data strategy, governance requirements, data product needs, and business priorities into scalable platforms, data services, standards, scorecards, and operating practices.

The role is accountable for data quality and scorecards, data governance and standards, data catalog, master data management, R&D data platforms, data ingestion and transformation services, data virtualization platforms, and cross-functional data products across Innovative Medicine R&D.

Key Responsibilities

Data Quality and Scorecards

* Define and operate data quality frameworks, scorecards, dashboards, thresholds, remediation routines, and executive reporting across priority R&D data domains and products.

* Partner with DDSAI (R&D Data Science Team), data owners, product teams, and business functions to define fit-for-purpose data quality rules, ownership, permitted use, and quality acceptance criteria.

* Establish automated quality monitoring for completeness, accuracy, timeliness, uniqueness, consistency, lineage, and domain-specific quality expectations.

* Translate data quality scorecard insights into remediation plans, product backlog priorities, governance decisions, and measurable improvements.

* Create transparency into data readiness for analytics, AI/GenAI, operational reporting, regulatory, safety, and scientific use cases.

Data Governance and Standards

* Implement data governance standards, decision rights, access workflows, data contracts, metadata expectations, permitted-use controls, lifecycle practices, and policy adherence across Cross R&D data systems.

* Partner with DDSAI data governance leaders, privacy, legal, Cybersecurity, quality, architecture, and business data owners to ensure governance is embedded into platforms and delivery workflows.

* Enforce standards for data domains, naming conventions, lineage, quality thresholds, stewardship, data sharing, retention, and compliant use.

* Establish governance routines that connect intake, prioritization, roadmap planning, data product ownership, standards compliance, and value realization.

* Enable consistent governance for structured, unstructured, semantic, operational, scientific, clinical, regulatory, and external data…