Mgr, Forward Deployed Engineer, Data & Intelligence

Johnson & Johnson Johnson & Johnson · Pharma · Hyderabad, Andhra Pradesh, India

Manager, Data Engineering & AI Platforms at Johnson & Johnson, Hyderabad. This role leads the development and modernization of enterprise Clinical Data and AI capabilities, focusing on scalable cloud-native data platforms, clinical data products, and AI/ML solutions including Generative AI and Agentic AI. Responsibilities include people leadership, product delivery, architecture oversight, and strategic technology management, transforming clinical data into AI-ready assets. The role involves building and optimizing data pipelines, developing data products, implementing AI/ML solutions, establishing AI governance, and collaborating with various stakeholders across Clinical Development, Medical Affairs, Regulatory, and R&D functions.

What you'd actually do

  1. Lead the engineering strategy and execution for Clinical Data Platforms supporting Clinical Operations, Data Management, Biostatistics, Medical Affairs, and Regulatory functions.
  2. Lead the design and implementation of enterprise-scale Clinical Data Lakehouse solutions using Databricks and modern cloud technologies.
  3. Lead implementation of AI-powered solutions that improve clinical trial efficiency, data review, patient insights, and operational decision-making.
  4. Lead Agile delivery teams utilizing Product Operating Model principles.
  5. Build, develop, and retain high-performing Data Engineering and AI teams.

Skills

Required

  • Cloud-native architectures
  • Data Product principles
  • Data Lakehouse solutions
  • Databricks
  • ETL/ELT pipelines
  • Data governance
  • Metadata management
  • Data quality
  • Interoperability
  • Machine Learning
  • Predictive Analytics
  • Generative AI
  • Agentic AI
  • Clinical Copilots
  • Intelligent Automation
  • Retrieval Augmented Generation (RAG)
  • AI governance
  • Responsible AI
  • MLOps
  • Agile delivery
  • People leadership
  • Team development
  • Technical standards
  • GxP
  • Computer System Validation (CSV)
  • HIPAA
  • GDPR

Nice to have

  • Clinical Trial Management Systems (CTMS)
  • Electronic Data Capture (EDC)
  • ePRO/eCOA platforms
  • Safety & Pharmacovigilance systems
  • Regulatory data sources
  • Real World Data (RWD)
  • Medical Affairs data platforms

What the JD emphasized

  • AI/ML solutions
  • Generative AI capabilities
  • Agentic AI platforms
  • Retrieval Augmented Generation (RAG) architectures
  • Responsible AI principles
  • MLOps best practices
  • GxP
  • Computer System Validation (CSV)
  • HIPAA
  • GDPR
  • J&J Data Privacy Standa

Other signals

  • 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.
  • Partner with Data Scientists and Product Teams to operationalize AI solutions using MLOps best practices.