Job Summary

As a Data Practice Leader, you are responsible for integrating innovation, technology, and business to develop an organization's data capabilities. This role combines technical expertise, strategic planning, and leadership. As a leader you will define and implement the enterprise's data strategy by building teams, applying best practices, and promoting the use of data & artificial intelligence for modern enterprises. Focuses on both immediate outcomes and long-term objectives while fostering a culture that supports experimentation, continuous learning, and operational excellence in alignment with enterprise data platform modernization goals.

This role involves shaping new opportunities, architecting data systems, advocating DataOps principles to the entire data lifecycle from data ingestion and transformation to storage and consumption, leading teams to deliver high-quality, scalable solutions while remaining directly involved in technical design and problem-solving

Key Responsibilities

Success criteria and KRA for this role are primarily aligned to business objectives, quantifiable outcomes, including but not limited to:

• Strategic Alignment and Vision –
  • Driving data strategy that aligns with the organization’s business objectives and vision
  • Articulate a roadmap for data maturity, encompassing immediate priorities and long-term aspirations
  • Ensure the strategy is adaptable to evolving business needs, technological advancements, and market trends
• Executive Stakeholder Engagement – Be the change agent for
  • Securing and sustaining buy-in from executive leadership, translating data concepts into business value propositions
  • Guiding the organization through cultural and operational transformations toward data-driven decision-making
  • Build bridges between IT, business units, and operations, ensuring alignment and shared ownership of data objectives & services
• Technical Mastery and Innovation –
  • Demonstrate deep proficiency in architecting, implementing, and optimizing cloud-based data platforms & hyper scalers
  • Drive adoption of modern data fabric architectures, data lakes, data warehouses, distributed computing, orchestration, semantic and advanced analytics platforms
  • Establish robust frameworks for data governance, metadata management, quality, and stewardship across the enterprise
• Leadership and Talent Building –
  • Build high-performing, multidisciplinary data teams (engineers, analysts, architects, principals, etc.,)
  • Invest in talent development through coaching, mentoring, and enabling continuous learning opportunities.
• Operational Excellence and Delivery –
  • Embed industry-leading best practices for data engineering, data management, analytics, data science, and AI development throughout the organization
  • Implement agile methodologies and DevOps practices to accelerate the development and deployment of data products and services
  • Track and demonstrate the tangible impact of data initiatives—cost savings, revenue growth, operational efficiencies, and customer satisfaction
  • Establish and monitor key performance indicators (KPIs) for data initiatives, tying them directly to business value
  • Tracking / measuring ROI on major data and AI investments

Skill Requirements

Essential Qualifications:

• Thought leader with 15+ years of experience in Cloud Data & Data engineering space with a minimum of 4+ years as Data practice leader and prior experience as a DWBI Principal/Solution Architect.
• Expert in designing and implementing enterprise data architectures and Analytical solutions.
• Proficient in defining and executing transformation strategy for legacy data & BI platforms
• Proficient in industrializing automation across data platforms leveraging AI/GenAI models
• Proficient in leveraging automation and DevOps practices to accelerate data operations, model development, and application/system maintenance
• Skilled (hands-on) in modern data orchestration tools, BI & Analytics platforms, Data Hyperscalers, Programming languages, Data Quality & Governance and Advance Analytical models / frameworks
• Processes solid understanding of Agile Manifesto and principles
• Proven ability to lead large teams and manage complex data programs.
• Should have good exposure to pre-sales & deal lifecycles
• Excellent written & verbal presentation skills, ability to present to technical & business audiences

Other Requirements