Manager, Forward Deployed Engineer, Data & Intelligence

Job description

**Sub Function** Clinical Data Platforms, Data Engineering & Artificial Intelligence **Reports to : Director, ICC** **Position Overview** Johnson & Johnson is seeking a highly motivated Manager, Data Engineering & AI Platforms to lead the development and modernization of enterprise Clinical Data and AI capabilities supporting Clinical Development, Medical Affairs, Regulatory, and other R&D functions. The role will be responsible for delivering scalable cloud-native data platforms, clinical data products, AI/ML solutions, and Generative AI capabilities that accelerate scientific insights, improve operational efficiency, and enable data-driven decision-making across the pharmaceutical development lifecycle. This position combines people leadership, product delivery, architecture oversight, and strategic technology management. The successful candidate will lead a team of engineers and collaborate with business stakeholders, clinical scientists, data management teams, biostatisticians, and digital product teams to transform fragmented clinical data into trusted, reusable, and AI-ready data assets. **Key Responsibilities** **Clinical Data Platform Leadership** - Lead the engineering strategy and execution for Clinical Data Platforms supporting Clinical Operations, Data Management, Biostatistics, Medical Affairs, and Regulatory functions. - Drive modernization of enterprise clinical data ecosystems using cloud-native architectures and Data Product principles. - Establish reusable clinical data services, ingestion frameworks, and standardized data models. - Partner with Clinical Development stakeholders to define technology roadmaps and prioritize platform investments. - Ensure scalability, performance, data quality, security, and operational excellence of clinical data solutions. **Data Engineering & Data Products** - Lead the design and implementation of enterprise-scale Clinical Data Lakehouse solutions using Databricks and modern cloud technologies. - Build and optimize ETL/ELT pipelines integrating diverse data sources including Clinical Trial Management Systems (CTMS), Electronic Data Capture (EDC), ePRO/eCOA platforms, Safety & Pharmacovigilance systems, Regulatory data sources, Real World Data (RWD), and Medical Affairs data platforms. - Develop reusable clinical data products that enable analytics, reporting, AI, and self-service consumption. - Drive best practices for data governance, metadata management, lineage, data quality, and interoperability. **Artificial Intelligence & Generative AI** - Lead implementation of AI-powered solutions that improve clinical trial efficiency, data review, patient insights, and operational decision-making. - Develop and operationalize Machine Learning solutions, Predictive Analytics, Generative AI applications, Agentic AI platforms, Clinical Copilots, Intelligent Automation solutions, and Retrieval Augmented Generation (RAG) architectures. - Establish AI governance frameworks aligned with Responsible AI principles and regulatory expectations. - Partner with Data Scientists and Product Teams to operationalize AI solutions using MLOps best practices. - Drive AI platform adoption across Clinical Development and R&D functions. **Product Delivery & Stakeholder Engagement** - Lead Agile delivery teams utilizing Product Operating Model principles. - Collaborate closely with Clinical Scientists, Data Managers, Biostatistics Teams, Medical Affairs, Regulatory Affairs, Product Managers, and Enterprise Architects. - Translate complex business and scientific requirements into scalable technology solutions. - Lead architecture reviews, technical design decisions, project execution, and risk mitigation activities. - Communicate effectively with executive leadership and business stakeholders. **People Leadership** - Build, develop, and retain high-performing Data Engineering and AI teams. - Establish engineering excellence practices, technical standards, and career development frameworks. - Foster a culture of innovation, accountability, collaboration, and continuous improvement. - Lead workforce planning, vendor management, hiring, and capability development activities. **Compliance, Security & Quality** - Ensure compliance with GxP, Computer System Validation (CSV), HIPAA, GDPR, J&J Data Privacy Standards, and AI Governance requirements. - Implement and maintain secure, compliant, and auditable platforms within regulated environments. - Partner with Quality, Compliance, and Security teams to ensure inspection and audit readiness. **Required Qualifications** **Education** - Bachelor's Degree in Computer Science, Engineering, Information Technology, Data Science, Bioinformatics, or a related field. - Master's Degree preferred. **Experience** - 10+ years of experience in Data Engineering, Data Platforms, Analytics, or Artificial Intelligence. - 5+ years of people leadership experience managing global engineering teams. - Experience delivering enterprise-scale cloud data platforms and modern analytics capabilities. - Proven experience implementing AI/ML and Generative AI solutions in production environments. - Experience working within Pharmaceutical, Biotechnology, Healthcare, or other regulated industries. - Demonstrated success managing cross-functional stakeholders and global delivery teams. **Technical Skills** **- Data Engineering** **- Cloud Technologies** **- Artificial Intelligence** **Clinical Domain Knowledge** - Databricks - Apache Spark - Delta Lake - SQL - Python - Data Modeling - ETL/ELT Frameworks - Data Lakehouse Architecture - Data Product Development - Azure (Preferred) - AWS - Cloud-native Data & AI Services - Infrastructure as Code (IaC) - DevOps & CI/CD - LLMs - Generative AI - Agentic AI - RAG - Vector Databases - MLOps - AI Governance - Machine Learning Engineering - Clinical Trial Data - Clinical Data Management - CDISC Standards (SDTM, ADaM) - Regulatory Data - Medical Affairs Data - Safety &