Manager, Forward Deployed Engineer, Data & Intelligence

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 & Pharmacovigilance RWD / RWE Clinical Analytics & Insights Preferred Qualifications Experience supporting Clinical Development, Clinical Data Management, or Pharmaceutical R&D organizations. Databricks, Azure, or AWS certifications. Experience building AI-enabled products and data platforms. Knowledge of Product Operating Model and Data Mesh principles. Experience leading digital transformation initiatives within healthcare or life sciences organizations. Engineering leader with expertise in Data Engineering, AI/ML and Generative AI. Strong experience with Databricks, Spark, Python, Azure/AWS and Lakehouse architectures. Experience building enterprise data platforms and AI-enabled solutions. Proven people leadership and stakeholder management experience. Healthcare, Life Sciences, Clinical Data or R&D domain experience preferred. What Impact Will You Have? As a Mgr, Forward Deployed Engineer, Data & Intelligence , you will play a critical role in advancing Johnson & Johnson's Clinical Data & AI strategy by delivering trusted, scalable, and AI-ready data platforms that accelerate insights, enhance clinical operations, and help bring life-changing therapies to patients faster.