Mgr, Forward Deployed Engineer, Data & Intelligence

Agile Technology; Hyderabad; On-site; INR 2,500,000 - 5,000,000; Full time

Job summary

Agile Technology in Hyderabad is seeking a senior leader to own the Clinical Data Platform strategy and delivery. You will architect cloud-native data ecosystems, build reusable data services, and partner with Clinical Operations to align technology roadmaps.

You will oversee data lakehouse and AI/ML initiatives, ensure governance, security, and quality in regulated environments, and mentor high-performing data engineering and AI teams across the globe.

Qualifications

• 10+ years of experience in data engineering, data platforms, analytics, or AI.
• 5+ years of people leadership, preferably managing global teams.
• Experience delivering enterprise-scale cloud data platforms and modern analytics capabilities.

Responsibilities

• Lead strategy and execution for clinical data platforms across functions.
• Design and operate ETL/ELT pipelines and data lakehouse architectures.
• Drive AI/ML initiatives including Generative AI and RAG applications.
• Lead Agile delivery and stakeholder engagement across global teams.
• Ensure data governance, quality, and security in regulated environments.

Skills

Databricks

Apache Spark

Delta Lake

SQL

Python

Data Modeling

ETL/ELT

Data Lakehouse

AI/ML

Regulatory knowledge

Education

Bachelor's degree in Computer Science / Engineering / IT

Masters degree preferred

Tools

Databricks

Azure

AWS

CI/CD

GxP tooling

Job description

Key Responsibilities 1. 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.

Key Responsibilities 2. 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)
  • Medical Affairs data platforms
• Develop reusable clinical data products supporting analytics, reporting, AI, and self-service consumption.
• Drive best practices for:
  • Data governance
  • Metadata management
  • Data lineage
  • Data quality
  • Data interoperability

Key Responsibilities 3. Artificial Intelligence & Generative AI

• Lead implementation of AI-powered solutions to 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
  • 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.

Key Responsibilities 4. 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
  • 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.

Key Responsibilities 5. 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
  • Continuous improvement
• Lead workforce planning, vendor management, hiring, and capability development activities.

Key Responsibilities 6. Compliance, Security & Quality

• Ensure compliance with:
  • GxP
  • Computer System Validation (CSV)
  • HIPAA
  • GDPR
  • J&J Data Privacy Standards
  • 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

• Bachelors Degree in:
  • Computer Science
  • Engineering
  • Information Technology
  • Data Science
  • Bioinformatics
  • or a related field
• Masters Degree preferred.

Professional Experience

• 10+ years of experience in Data Engineering, Data Platforms, Analytics, or Artificial Intelligence.
• 5+ years of people leadership experience, preferably 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, Life Sciences, or other regulated industries.
• Demonstrated success managing cross-functional stakeholders and global delivery teams.

Technical Skills Data Engineering

• Databricks
• Apache Spark
• Delta Lake
• SQL
• Python
• Data Modeling
• ETL / ELT Frameworks
• Data Lakehouse Architecture
• Data Product Development

Cloud & Platform Engineering

• Azure - Preferred
• AWS
• Cloud-native Data & AI Services
• Infrastructure as Code (IaC)
• DevOps
• CI/CD

Artificial Intelligence & Machine Learning

• Machine Learning Engineering
• Large Language Models (LLMs)
• Generative AI
• Agentic AI
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• MLOps
• AI Governance
• Predictive Analytics
• Intelligent Automation

Clinical Domain Knowledge

Candidates should have knowledge or experience in one or more of the following:

• Clinical Trial Data
• Clinical Data Management
• CDISC Standards
  • SDTM
  • ADaM
• Regulatory Data
• Medical Affairs Data
• Safety & Pharmacovigilance
• Real-World Data (RWD)
• Real-World Evidence (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.
• Experience working in highly regulated environments with strong understanding of data privacy, security, quality, and compliance requirements.

Leadership & Behavioral Competencies

The ideal candidate should demonstrate:

• Strong people and engineering leadership
• Strategic thinking and technology vision
• Product-oriented mindset
• Strong stakeholder management
• Excellent communication and influencing skills
• Ability to work with global and cross-functional teams
• Strong problem-solving and decision-making capabilities
• Ownership and accountability
• Innovation mindset
• Ability to operate effectively in complex, regulated environments

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