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 MedTech, 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 more at jnj.com
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Job Function:
Data Analytics & Computational SciencesJob Sub Function:
Data EngineeringJob Category:
Scientific/TechnologyAll Job Posting Locations:
Horsham, Pennsylvania, United States of America, Titusville, New Jersey, United States of AmericaJob Description:
About Innovative Medicine
Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.
Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
Learn more at https://www.jnj.com/innovative-medicine
Prefered Location:
Horsham, PA or Titusville, NJ. Remote work will considered on a case by case basis.
Role Overview
We are seeking a Principal Data Engineer to provide technical leadership within Global Medical Safety (GMS), supporting the Safety Analytics organization. This role is focused on building and enabling modern safety analytics tools using AI, Machine Learning, and GenAI, underpinned by robust, compliant, and scalable data engineering on Google Cloud Platform (GCP).
The Principal Data Engineer is responsible for end-to-end ownership of safety analytics data engineering, spanning data intake, data quality and continuity, pipeline and architecture design, automation, performance optimization, and compliance. The role enables advanced analytical, machine learning, and predictive capabilities for pharmacovigilance and serves as a technical data engineering leader within Global Medical Safety.
This is a Principal-level individual contributor role with broad technical influence, working closely with safety scientists, analytics teams, data scientists, IT, and platform partners to deliver trusted, production-grade analytics capabilities for safety decision-making.
Key Responsibilities
Safety Analytics & Pharmacovigilance Enablement
Design and maintain production-grade data pipelines and curated datasets that directly support pharmacovigilance activities, including safety monitoring, analytics, and regulatory reporting.
Ensure data engineering solutions produce reproducible, explainable, and trusted analytics outputs suitable for safety decision support and inspection readiness.
Enable AI/ML and GenAI workflows for safety analytics, including:
End-to-End Data Architecture & Lifecycle Ownership
Own the end-to-end data lifecycle for safety analytics, from source system intake through transformation, serving, and downstream analytical consumption, ensuring data continuity, traceability, and integrity.
Lead architectural decisions across ingestion, transformation, storage, and serving layers on GCP (e.g., BigQuery, Dataform, object storage).
Design, implement, and automate scalable, reusable data pipelines and architectures to support evolving safety analytics needs.
Data Quality, Governance & Compliance
Establish and enforce data quality, validation, lineage, and observability standards for safety analytics datasets.
Define and implement data governance practices, including data contracts, schema versioning, access control, stewardship, and lifecycle management.
Ensure safety analytics data and systems meet Global Medical Safety requirements for reliability, auditability, and regulatory use.
GxP Validation & Regulatory Readiness
Apply GxP validation expertise to data pipelines, analytics services, and supporting infrastructure.
Partner with quality and compliance teams to implement CSV/CSA-aligned controls, audit trails, documentation, and organizational change.
Balance delivery velocity and innovation with the rigor required for regulated pharmacovigilance systems.
Services, APIs & Microservices
Design and build APIs and microservices-based architectures to operationalize safety analytics and ML capabilities (e.g., feature serving, retrieval services, analytics backends).
Deploy and operate services on GCP (e.g., Cloud Run, GKE) with a strong focus on security, scalability, and observability.
Enforce contract-first integration patterns between producing and consuming systems to ensure reliability and safe evolution.
Infrastructure, CI/CD & Cost Optimization
Provision and manage cloud infrastructure using Terraform (Infrastructure as Code) on GCP.
Build and maintain CI/CD pipelines (e.g., Jenkins) for data pipelines, analytics services, feature pipelines, and ML data assets.
Continuously optimize the performance and cost efficiency of data and analytics infrastructure while maintaining compliance and reliability standards.
Technical Leadership & Stakeholder Engagement
Serve as a technical authority and data engineering leader for Safety Analytics within Global Medical Safety.
Review and influence designs across pipelines, services, feature stores, and AI/ML integrations to maintain a high technical bar. Collaborate closely with safety scientists, epidemiologists, biostatisticians, analytics teams, IT, and platform partners to translate safety needs into scalable technical solutions.
Communicate complex technical concepts and tradeoffs clearly to both technical and non-technical stakeholders.
Enable and upskill teams through mentorship, guidance, and knowledge sharing on modern data, cloud, and AI technologies.
Qualifications
Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience) is required.
5+ years of experience in data engineering or analytics engineering with increasing responsibilities.
Proficient programming skills in Python and SQL.
Deep understanding of data architecture for analytics and ML (e.g., batch/streaming, modeling, performance optimization).
Proven ability to translate complex problems into clear, concise, and testable programming code/tools.
Experience implementing data contracts, data validation, schema versioning, and governance practices, as well as a solid understanding of leading cloud concepts (GCP preferred).
Experience designing and operating APIs and microservices-based architectures.
Excellent written and verbal communication, customer service, interpersonal, and teamwork skills to foster a collaborative team environment.
Solid understanding of SDLC and Agile methodologies, alongside basic project management skills.
Experience building production workloads on Google Cloud Platform (GCP) is preferred.
Experience provisioning infrastructure using Terraform (Infrastructure as Code) and building CI/CD pipelines (e.g., Jenkins) is preferred.
Experience in pharmaceuticals, life sciences, healthcare, or a related regulated domain is preferred.
GCP certification is preferred.
Experience enabling AI/ML and GenAI workflows (e.g., feature engineering, RAG patterns, semantic retrieval) for analytical applications is preferred.
Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please
contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your
accommodation resource.
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Required Skills:
Preferred Skills:
Advanced Analytics, Agility Jumps, Coaching, Critical Thinking, Data Engineering, Data Governance, Data Modeling, Data Privacy Standards, Data Science, Digital Fluency, Execution Focus, Hybrid Clouds, Organizing, Presentation Design, Technical Development, Technical Writing, Technologically Savvy
The anticipated base pay range for this position is :
$102,000.00 - $177,100.00Additional Description for Pay Transparency:
Subject to the terms of their respective plans, employees are eligible to participate in the Company’s