Director of Data & AI Engineering

We are seeking a highly experienced and technically strong leader to head our Data & AI Engineering function. This role will be responsible for driving the technical vision, delivery excellence, and AI-first transformation across our data engineering and analytics teams.

The ideal candidate will bring a hands-on leadership approach, combining deep expertise in data platforms and applied AI with the ability to guide teams, architect scalable solutions, and deliver measurable business outcomes.

Role Summary:

This position requires a strategic yet hands-on leader who can operate across data engineering, analytics, and AI, and drive the organization toward becoming a truly AI-native delivery function. The role demands a balance of technical depth, leadership capability, and business acumen to deliver impactful, scalable, and future-ready solutions.

Key Responsibilities:

• Define and implement the AI-first engineering strategy, including standards, frameworks, and best practices across all engagements
  


• Lead, mentor, and scale a cross-functional team of data engineers, analysts, and integration specialists
  


• Drive adoption of AI-assisted development tools (e.g., Cursor, Claude Code, GitHub Copilot) as an integral part of the engineering workflow
  


• 
  
  
  Design and deliver advanced AI solutions, including:
  
  
  
  
  
  
  • LLM integrations ( Large Language Model)
    
  
  
  • Prompt engineering frameworks
    
  
  
  • Agentic workflows
    
  
  
  • RAG-based architectures
    
  
  


• Architect and oversee end-to-end data solutions, including cloud data platforms, ERP integrations, and reporting systems
  


• Act as the technical authority, providing hands-on guidance through solution design, code reviews, and engineering best practices
  


• Collaborate with internal stakeholders and clients to identify opportunities for AI-driven optimization and automation
  


• Establish and enforce data governance, quality standards, and responsible AI practices.
  

Required Experience

• 10+ years of experience in data engineering, analytics, or data platform development
  


• Minimum 5 years of hands-on experience in applied AI/ML, including LLMs and modern AI frameworks
  


• Proven, day-to-day experience with AI-assisted development tools (such as Cursor, Claude Code, GitHub Copilot)
  


• Demonstrated success in leading technical teams within consulting or managed services environments
  


• Strong ability to translate technical solutions into business value for stakeholders.
  

Mandatory Key Skills

Core Technical Skills

• Strong proficiency in Python and SQL (including stored procedures)
  


• Hands-on experience with cloud data platforms (Azure, Snowflake, Databricks)
  


• Expertise in building and managing ETL/ELT pipelines
  


• Experience with business intelligence tools (Power BI, Tableau, Looker)
  

AI & Advanced Capabilities

• 
  
  
  Deep understanding of:
  
  
  
  
  
  
  • Large Language Models (LLMs)
    
  
  
  • Prompt engineering techniques
    
  
  
  • RAG (Retrieval-Augmented Generation) architectures
    
  
  
  • Agentic AI frameworks
    
  
  


• Experience designing and deploying production-grade AI solutions
  


• Regular usage of AI-assisted development tools in coding and delivery workflows
  

Leadership & Stakeholder Skills

• Proven experience in team leadership, mentoring, and capability building
  


• Strong architecture and code review expertise
  


• Ability to communicate effectively with both technical and non-technical stakeholders
  

Business & Consulting Orientation

• Strong problem-solving skills with the ability to convert business requirements into scalable technical solutions
  


• Experience in client-facing roles and consulting environments
  


• Ability to articulate business impact and ROI of data and AI initiatives
  

Preferred Qualifications (Good to Have)

• Experience with ERP platforms (SAP, Dynamics, Plex)
  


• Familiarity with workflow automation tools (e.g., n8n)
  


• Background in leading analytics consulting firms (e.g., Tiger Analytics, Fractal, Tredence)
  


• 
  
  
  Contributions to open-source AI or data engineering projects.
  
  

below are the Mandatory skill sets

• Strong programming expertise in Python and SQL (including stored procedures)
  


• Hands-on experience in building and managing ETL/ELT data pipelines
  


• Experience with cloud data platforms (Azure, Snowflake, Databricks)
  


• Solid understanding of data architecture and end-to-end data engineering workflows
  


• 
  
  
  Proven hands-on experience with Applied AI, including:
  
  
  
  
  
  
  • Large Language Models (LLMs)
    
  
  
  • Prompt Engineering
    
  
  
  • RAG (Retrieval-Augmented Generation) architectures
    
  
  
  • Agentic AI / workflow frameworks
    
  
  


• Demonstrated experience in building and deploying AI solutions in production environments
  


• 
  
  
  Regular, hands-on usage of AI-assisted development tools such as:
  
  
  
  
  
  
  • Cursor
    
  
  
  • Claude Code
    
  
  
  • GitHub Copilot
    
  
  


• 
  
  
  Experience in technical leadership, including:
  
  
  
  
  
  
  • Leading/mentoring engineering teams
    
  
  
  • Solution architecture and design
    
  
  
  • Code reviews and technical governance
    
  
  


• Strong understanding of data + analytics ecosystem, including BI tools (Power BI, Tableau, or Looker)
  


• Experience working in client-facing or consulting environments
  


• Ability to translate business requirements into scalable technical solutions
  


• Strong communication and stakeholder management skills, including explaining technical concepts to non-technical audiences