Associate Director, Safety Data Solutions Architect
Compensation
Not disclosed
Location
Horsham, Pennsylvania, United States of America
Work setup
Not specified
Seniority
Not specified
Employment
Contract
Experience
3+ years
Category
Architecture
Posted
Skills
ai
analytics
api
automation
bigquery
ci-cd
cloud
cloud-run
data-analytics
data-modeling
data-pipelines
data-quality
data-science
data-visualization
dataform
embeddings
event-driven-architecture
feature-engineering
finops
gcp
generative-ai
gke
infrastructure-as-code
llm
machine-learning
microservices
mlops
observability
secrets-management
stakeholder-management
terraform
togaf
vertex-ai
zero-trust
Must have
10+ years in data/analytics engineering and architecture, including 3+ years in solution/enterprise architecture roles.
Demonstrated leadership coordinating Principal/Senior engineers and cross-functional teams in regulated environments.
Deep architecture experience on GCP: BigQuery, Dataform, Cloud Storage; orchestration and automation; familiarity with Pub/Sub, Dataflow; services on Cloud Run and/or GKE.
Strong data modeling for analytics and ML (batch and streaming), performance optimization, and observability practices.
Proven experience implementing data contracts, validation, schema versioning, lineage/metadata, and access control.
Hands-on understanding of AI/ML and GenAI patterns for analytics (feature engineering, vector stores, semantic retrieval, RAG) with emphasis on explainability and controls; partner with SA Data Scient
GxP/CSV/CSA experience for data and analytics platforms; audit readiness and change control.
Excellent communication and stakeholder management; ability to simplify complex topics and influence senior leaders.
Nice to have
Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).
Experience in pharmaceuticals, life sciences, healthcare, or related regulated domains.
Experience with Terraform (Infrastructure as Code) and CI/CD; policy-as-code.
Exposure to feature store enablement and MLOps on GCP; familiarity with Vertex AI a plus.
Certifications: Google Professional Cloud Architect or Professional Data Engineer; TOGAF; SAFe
FinOps experience, including budget management and efficiency tracking for cloud analytics workloads.
The anticipated base pay range for this position is :
Additional Description for Pay Transparency:
Full description
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
As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.
Job Function:
Data Analytics & Computational SciencesJob Sub Function:
Data ScienceJob 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
Role Overview
Johnson & Johnson Global Medical Safety (GMS) is seeking an Associate Director, Safety Data Solutions Architect to lead the target architecture, standards, and delivery roadmap for safety analytics on Google Cloud Platform (GCP). This role provides solution architecture leadership for pharmacovigilance and safety analytics, translating safety science needs into validated, scalable, and compliant data and AI capabilities. Partner with Safety Analytics (SA) Data Scientists on LLM/GenAI use cases to ensure platform guardrails, retrieval/inference patterns, and compliance controls. The Architect will coordinate Principal-level data engineers and cross-functional teams to deliver trusted, inspection-ready data products for downstream analytics and AI services. The role emphasizes architecture strategy, regulatory readiness, and responsible AI, while ensuring alignment to enterprise patterns, cost efficiency, and operating excellence. A selective hands-on component focuses on reference implementations and “golden-path” templates that accelerate team adoption.
Key Responsibilities
Translate architecture strategy into measurable outcomes by establishing baselines, performance indicators, and benefit-realization measures for data onboarding speed, solution reuse, platform reliability, inspection readiness, cost efficiency, and time to insight for safety scientists.
Partner with Safety, Product, Data Science, and Technology leaders to translate business capabilities and scientific workflows into a multi-year data and platform roadmap, including build-versus-buy recommendations, investment sequencing, adoption and value measures, and the rationalization and retirement of legacy technologies.
Establish governed AI lifecycle patterns and platform controls for the evaluation, approval, versioning, deployment, monitoring, and reproducibility of AI-enabled solutions, including defined human oversight, provider portability, rollback mechanisms, and controlled use of models, prompts, retrieval sources, and agent tools; maintain clear accountability boundaries between platform governance and scientific ownership of model behavior.
Define domain-aligned data products and curated datasets for pharmacovigilance (signal detection, case analytics, predictive safety) with clear quality, reliability, and inspection-readiness criteria.
Own target-state and transitional architectures across ingestion, transformation, storage, serving, and consumption on GCP (e.g., BigQuery, Dataform, Cloud Storage); drive reuse via reference architectures and patterns.
Set guardrails for AI/ML and GenAI integrations (embeddings, vector stores, semantic retrieval, RAG) with emphasis on explainability, traceability, and responsible AI; partner with SA Data Scientists without overlapping model development.
Establish canonical data models, data contracts, and lifecycle practices; implement contract-first integration, schema versioning, and controlled interface evolution across producers/consumers.
Chair design reviews; approve solution designs and enforce non-functional requirements (resilience, scalability, security, observability, SLOs); remove delivery blockers and ensure quality and compliance.
Drive data quality, governance, and observability, including validation standards, lineage/metadata, privacy and security controls (least privilege, data minimization, PII/PHI protections), and clear R&D vs. production pathways.
Define standards for APIs, microservices, and retrieval services on GCP (e.g., Cloud Run, GKE); establish reliability and security baselines (SLO/SLA targets, error budgets, zero trust, secrets management, telemetry).
Promote event-driven and streaming architectures (e.g., Pub/Sub, Dataflow) with contract-first integration, backward-compatible evolution, and robust monitoring.
Partner with SA Data Scientists and MLOps to define contract-first model and inference interfaces (batch/online), including rate limits, cost controls, telemetry, and audit logging; SA Data Scientists retain ownership of prompt design and model behavior.
Govern CI/CD for data pipelines and analytics/retrieval services; embed policy-as-code, testing, artifact integrity, and promotion gates; own cost governance (budgets, showback/chargeback, efficiency targets, right-sizing, usage policies).
Coordinate Principal-level engineers’ scope and priorities across pipelines, services, feature stores, and AI/ML integrations; manage cross-team dependencies; communicate decisions to technical and non-technical audiences; mentor teams and uplift standards.
Hands-on (selective): Deliver and maintain reference implementations and design spikes (e.g., ingestion to BigQuery, contract-first schemas, Cloud Run service scaffolds, Pub/Sub/Dataflow patterns) to de-risk delivery and accelerate adoption.
Required
10+ years in data/analytics engineering and architecture, including 3+ years in solution/enterprise architecture roles.
Demonstrated leadership coordinating Principal/Senior engineers and cross-functional teams in regulated environments.
Deep architecture experience on GCP: BigQuery, Dataform, Cloud Storage; orchestration and automation; familiarity with Pub/Sub, Dataflow; services on Cloud Run and/or GKE.
Strong data modeling for analytics and ML (batch and streaming), performance optimization, and observability practices.
Proven experience implementing data contracts, validation, schema versioning, lineage/metadata, and access control.
Hands-on understanding of AI/ML and GenAI patterns for analytics (feature engineering, vector stores, semantic retrieval, RAG) with emphasis on explainability and controls; partner with SA Data Scientists without owning model development.
GxP/CSV/CSA experience for data and analytics platforms; audit readiness and change control.
Excellent communication and stakeholder management; ability to simplify complex topics and influence senior leaders.
Preferred
Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).
Experience in pharmaceuticals, life sciences, healthcare, or related regulated domains.
Experience with Terraform (Infrastructure as Code) and CI/CD; policy-as-code.
Exposure to feature store enablement and MLOps on GCP; familiarity with Vertex AI a plus.
Certifications: Google Professional Cloud Architect or Professional Data Engineer; TOGAF; SAFe
FinOps experience, including budget management and efficiency tracking for cloud analytics workloads.
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.
#LI-GR1
#LI-Hybrid #JNJDataScience
Required Skills:Preferred Skills:
Advanced Analytics, Consulting, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Mentorship, Strategic Thinking, Tactical Planning, Technical CredibilityThe anticipated base pay range for this position is :
$137,000.00 - $235,750.00Additional Description for Pay Transparency:
Subject to the terms of their respective plans, employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).
This position is eligible to participate in the Company’s long-term incentive program.
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
Vacation –120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
Holiday pay, including Floating Holidays –13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave – 80 hours in a 52-week rolling period10 days
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year
For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits