Data & AI CoE / Practice Lead

Role Overview

We are seeking a commercially driven Data & AI Practice Leader to drive digital transformation across enterprise applications, data platforms, and AI-enabled business solutions.

Responsibilities

1. Practice Strategy and P&L Ownership

• Define and execute Data & AI practice strategy across APAC markets.
• Drive revenue growth, pipeline expansion, and profitable delivery.
• Develop go-to-market strategies for modernization and AI transformation services.

2. Drive Enterprise Modernization Programs

Lead transformation initiatives across:

Applications & Systems Modernization

• Legacy application modernization
• Cloud-native architecture adoption
• Microservices and API-driven platforms
• Digital platform engineering

Data Modernization

• Enterprise data platforms
• Data lake / lakehouse architecture
• Data governance and MDM
• Real-time analytics

AI & GenAI Transformation

• Enterprise AI strategy
• GenAI use case implementation
• Intelligent automation and decision intelligence

Technology exposure preferred:

• Amazon Web Services
• Microsoft Azure
• Google Cloud

3. Client Advisory

• Lead client conversations at CxO level (CIO, CTO, CDO, Chief Digital Officer).
• Lead RFP, solution design, and commercial proposal development.
• Position FPT as a strategic transformation partner.

4. Delivery and Architecture Governance

• Provide oversight across large transformation programs.
• Ensure quality, risk, compliance, and delivery excellence.
• Guide architecture and design decisions across delivery streams.

5. Build CoE Assets and Innovation

• Develop reusable accelerators for:
• Data platforms
• AI solutions
• Modernization frameworks
• Industry-specific solutions

Drive partnerships with leading technology ecosystem providers.

Requirements:

• 15+ years of experience in Data, AI, or Application Modernization.
• Experienced in consulting or system integration environments.
• Experience leading large-scale transformation programs.
• Strong commercial and client engagement experience.
• MBA or advanced technical/AI qualifications.
• Certifications in cloud or AI platforms.
• Strong knowledge across multiple areas:

Data Engineering & Platforms

• Data lake / warehouse / lakehouse architectures
• ETL / streaming pipelines
• Data governance and quality

AI & GenAI

• Machine learning platforms
• LLM / GenAI solution implementation
• Intelligent automation

Application Modernization

• Cloud-native application design
• API and microservices architecture
• Legacy system transformation

Preferred exposure to:

• Databricks
• Snowflake
• Microsoft Fabric ecosystem