Key Responsibilities :

Practice & Business Leadership :

- Define and execute the strategic vision and growth roadmap for the Data & AI practice.

- Build and scale high-performing data, analytics, AI, and engineering teams.

- Drive multi-year enterprise transformation programs and strategic client engagements.

- Identify new business opportunities and contribute to proposals, solutioning, and client acquisition.

- Develop reusable frameworks, accelerators, and industry-specific Data & AI offerings.

Client & Executive Management:

- Act as a senior strategic advisor to C-suite executives and enterprise stakeholders.

- Lead executive-level discussions around Data & AI transformation, technology strategy, and business value.

- Own strategic client relationships and serve as the ultimate escalation point for critical engagements.

- Translate business challenges into scalable technology and transformation roadmaps.

- Drive customer satisfaction, retention, and expansion across strategic accounts.

Data & AI Architecture:

- Provide architectural leadership across modern enterprise data ecosystems.

- Drive solutions leveraging Snowflake, Databricks, Azure Data Factory (ADF), and modern cloud data platforms.

- Establish scalable data architectures, data pipelines, integration frameworks, and analytics platforms.

- Oversee data governance, quality, lineage, observability, and security initiatives.

- Provide strategic direction on platforms and tools such as Collibra, Alation, and Monte Carlo.

- Drive enterprise AI/ML readiness, including MLOps, vector databases, Generative AI, and LLM-based solutions.

- Ensure AI solutions are scalable, secure, governed, and aligned with enterprise architecture.

Delivery & Operational Excellence :

- Oversee global delivery across multiple programs, geographies, and client environments.

- Establish delivery governance, engineering standards, KPIs, and quality frameworks.

- Ensure programs meet business objectives, timelines, budgets, and quality expectations.

- Drive continuous improvement, automation, and operational excellence across the practice.

- Mentor senior architects, engineering leaders, and delivery heads.

Required Skills & Experience :

- 20-25 years of progressive experience in IT services, consulting, technology, or global delivery leadership.

- Proven experience leading a Data & AI practice or large-scale Data/Analytics organization.

- Strong expertise in enterprise data architecture and modern cloud data platforms.

- Hands-on architectural exposure to Snowflake, Databricks, and Azure Data Factory.

- Strong understanding of data governance, data quality, lineage, and observability.

- Experience with platforms such as Collibra, Alation, or Monte Carlo is preferred.

- Strong understanding of AI/ML, MLOps, Generative AI, LLMs, and vector databases.

- Proven experience managing large, complex, multi-year transformation programs.

- Strong commercial, consulting, and solutioning capabilities.

- Excellent executive communication, stakeholder management, negotiation, and presentation skills.

Preferred Candidate Profile :

- Experience working with global enterprise clients and distributed delivery teams.

- Strong C-suite engagement and executive advisory experience.

- Proven track record of building and scaling technology practices.

- Ability to balance business strategy, technology architecture, delivery excellence, and revenue growth.

- Strong understanding of emerging Data & AI trends and enterprise adoption challenges.