Managing Director - Data and Analytics

Lead Lloyds' data and analytics capability in India: modernize the data estate, strengthen data governance and quality, and scale analytics and insight that drive better decisions, customer outcomes and regulatory compliance.

Key responsibilities

• Set the India data and analytics strategy, aligned to the Group data strategy and architecture (data platforms, products, mesh/fabric, cloud migration).
• Lead data engineering, data platform, BI/analytics, advanced analytics, data governance, data quality, metadata and master/reference data teams.
• Deliver enterprise data products and platforms that serve business, risk, finance, regulatory reporting and AI use cases.
• Own data governance, lineage, privacy and quality controls, including BCBS 239 principles, regulatory reporting and data-protection compliance.
• Drive modernization: legacy data warehouse decommissioning, cloud data platforms, real-time streaming, self-service analytics.
• Partner with business, risk, finance and technology leaders to priorities data use cases and embed data-driven decision making.
• Optimize cost, vendor and platform spend; manage workforce, budget and benefits realization.
• Build data talent and a culture of data literacy and data ownership.

Qualifications and experience

• 18+ years in data, analytics or technology, with 8+ years in senior data leadership in banking or financial services.
• Demonstrated delivery of large-scale data platform modernization or cloud migration in a regulated bank.
• Deep knowledge of data governance, data quality, lineage and regulatory data requirements.
• Experience leading large teams (500+ preferred) across engineering, analytics and governance.
• Degree in engineering, computer science, statistics or related field; MBA a plus.

Must-have: enterprise data platform or data governance delivery in BFSI; cloud data migration experience; regulatory data exposure (BCBS 239, regulatory reporting); team of 300+.

Good-to-have: data-product or data-mesh implementation; experience across multiple domains (retail, risk, finance); experience bridging data and AI programmes.