Associate Director, Safety Data Solutions Architect

Johnson & Johnson

. Lead target architecture, standards, and delivery roadmap for safety analytics on Google Cloud Platform .

Posted 10/27/2026full-timeUnited StatesSenior💰 $137,000 - $235,750 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in data and analytics engineering, particularly in leading solution architecture on Google Cloud Platform. Proficient in developing scalable, compliant data products and AI capabilities while ensuring data quality, governance, and performance optimization.

Highest-signal resume keywords

Google Cloud Platform ArchitectureData Modeling for Analytics and MLLeadership in Regulated EnvironmentsAI/ML and GenAI Patterns for AnalyticsGxP/CSV/CSA Compliance Experience

ATS Keywords

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Hard Skills

Data EngineeringSolution ArchitectureData Contracts ImplementationPerformance OptimizationSchema VersioningMetadata ManagementAI/ML Feature EngineeringStreaming Data ProcessingCloud Cost GovernanceData Quality Assurance

Soft Skills

Excellent CommunicationStakeholder ManagementInfluencing Senior Leaders

Tools & Technologies

BigQueryDataformCloud StorageTerraformCI/CDPolicy-as-CodePub/SubDataflowCloud RunGKE

Certifications & Qualifications

Google Professional Cloud ArchitectProfessional Data EngineerTOGAFSAFe

Industry Keywords

PharmaceuticalsLife SciencesHealthcareRegulated DomainsGxPCSVCSAAudit ReadinessChange ControlFinOps

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud PlatformMicroservicesTerraform

About the role

Key responsibilities & impact

Lead target architecture, standards, and delivery roadmap for safety analytics on Google Cloud Platform
Provide solution architecture leadership for pharmacovigilance and safety analytics
Translate safety science needs into validated, scalable, and compliant data and AI capabilities
Partner with Safety Analytics Data Scientists on LLM/GenAI use cases, platform guardrails, retrieval/inference patterns, and compliance controls
Coordinate Principal-level data engineers and cross-functional teams to deliver trusted, inspection-ready data products
Establish architecture baselines, performance indicators, and benefit-realization measures
Develop multi-year data and platform roadmaps, build-versus-buy recommendations, investment sequencing, and legacy technology rationalization
Define governed AI lifecycle patterns and platform controls for AI-enabled solutions
Define domain-aligned pharmacovigilance data products and curated datasets
Own target-state and transitional architectures across ingestion, transformation, storage, serving, and consumption on GCP
Establish canonical data models, data contracts, lifecycle practices, schema versioning, and controlled interface evolution
Chair design reviews and enforce resilience, scalability, security, observability, and SLO requirements
Drive data quality, governance, lineage, metadata, privacy, security, and inspection readiness
Define standards for APIs, microservices, retrieval services, event-driven architectures, and streaming on GCP
Partner with Data Scientists and MLOps on model and inference interfaces, cost controls, telemetry, and audit logging
Govern CI/CD for data pipelines and analytics/retrieval services, including policy-as-code, testing, artifact integrity, and promotion gates
Own cloud cost governance, budgets, showback/chargeback, efficiency targets, and right-sizing
Coordinate Principal-level engineers, manage cross-team dependencies, communicate decisions, and mentor teams
Deliver selective reference implementations and design spikes to accelerate adoption

Requirements

What you’ll need

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, including feature engineering, vector stores, semantic retrieval, and RAG
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
Experience in pharmaceuticals, life sciences, healthcare, or related regulated domains preferred
Experience with Terraform, Infrastructure as Code, CI/CD, and policy-as-code preferred
Exposure to feature store enablement and MLOps on GCP; familiarity with Vertex AI a plus
Google Professional Cloud Architect, Professional Data Engineer, TOGAF, or SAFe certifications preferred
FinOps experience preferred
Master’s degree in Computer Science, Engineering, or related field, or equivalent experience preferred

Benefits

Comp & perks

Consolidated retirement plan (pension)
Savings plan (401(k))
Long-term incentive program
Vacation – 120 hours per calendar year
Sick time – 40 hours per calendar year; 48 hours for employees residing in Colorado; 56 hours for employees residing in Washington
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 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 period
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year
Inclusive interview accommodations for applicants with disabilities