Vertical Head AI and Data Warehouse

Yes Bank Ltd.; Mumbai; On-site; INR 3,000,000 - 7,000,000; Full time

Job summary

Yes Bank Ltd. in Mumbai seeks a senior leader to head the AI, Advanced Analytics, and Data Warehouse function, defining enterprise data strategy, governing data assets, and driving adoption of modern analytics across the organization.

The role requires steering data modernization, cloud platforms, and AI capabilities, with accountability for enterprise data platforms, BI, governance, and analytics programs across risk, compliance, and business units.

Qualifications

• 20+ years of experience in Data Warehousing, BI, Data Engineering, Analytics or Enterprise Data Platforms.
• Minimum 7–10 years of leadership experience managing enterprise data, analytics, AI, or BI functions.
• Proven experience designing and implementing enterprise data warehouse, data lake, cloud data platforms, and analytics solutions.
• Strong expertise in AI, ML, Predictive Analytics, BI, and data governance frameworks.
• Experience with modern data platforms including Snowflake, Databricks, Hadoop, Teradata, and cloud services.

Responsibilities

• Define and execute the enterprise AI, Data Warehouse, and Analytics strategy.
• Lead development and deployment of AI, ML, Predictive Analytics, and Generative AI solutions.
• Oversee design and modernization of enterprise data warehouses and data lakes.
• Govern data integration, ETL/ELT, and master data management.
• Enable enterprise reporting, dashboards, and self-service analytics.
• Mentor and lead Data Architects, Engineers, Scientists, and Analysts.

Skills

AI Leadership

Data Strategy

Cloud Modernization

Leadership & Mentoring

Data Governance

Tools

Snowflake

Databricks

Hadoop

Teradata

Oracle

SQL Server

Azure Data Platform

AWS Data Services

Google Cloud Data Platforms

Job description

Role Summary: To lead the Bank's Artificial Intelligence (AI), Advanced Analytics, and Data Warehouse function by establishing enterprise data platforms, AI capabilities, and analytics solutions that enable data-driven decision-making, operational efficiency, regulatory compliance, and business innovation. The role is responsible for defining the data and AI strategy, governing enterprise data assets, and driving the adoption of modern analytics and AI technologies across the organization.

Strategy and Planning

• Define and execute the enterprise AI, Data Warehouse, and Analytics strategy aligned with the Bank's business and digital transformation objectives.
• Establish a roadmap for data modernization, enterprise data platforms, business intelligence, advanced analytics, machine learning, and AI capabilities.
• Drive the adoption of cloud-based data platforms, data lakes, real-time analytics, and AI-driven business solutions.
• Partner with Business, Technology, Risk, Compliance, Data Governance, and Information Security teams to identify high-value data and AI use cases.

AI & Advanced Analytics Leadership

• Lead development and deployment of AI, Machine Learning, Predictive Analytics, and Generative AI solutions.
• Identify business opportunities for AI adoption across customer, operational, risk, and compliance domains.
• Drive enterprise AI innovation and value realization programs.

Enterprise Data Warehouse Management

• Oversee design, implementation, enhancement, and maintenance of enterprise data warehouse platforms.
• Ensure availability, scalability, integrity, and performance of data warehouse environments.
• Lead modernization initiatives involving cloud data warehousing, data lakes, and enterprise analytics platforms.

Data Engineering & Data Management

• Govern data integration, ETL/ELT processes, master data management, and enterprise data architecture.
• Ensure high-quality, trusted, and accessible enterprise data assets.

Business Intelligence & Reporting

• Enable enterprise reporting, dashboards, self-service analytics, and management information systems.
• Drive data-driven decision-making through advanced visualization and business intelligence capabilities.

People Management

• Lead and manage teams comprising Data Architects, Data Engineers, AI/ML Engineers, Data Scientists, BI Developers, Data Analysts, and Data Governance Specialists.
• Define organizational structure, workforce planning, succession planning, and capability development programs.
• Mentor technical leaders and provide strategic direction on data architecture, analytics, AI, and modern data platforms.

Essential

• 20+ years of experience in Data Warehousing, Business Intelligence, Data Engineering, Data Management, Analytics, Artificial Intelligence, or Enterprise Data Platforms.
• Minimum 7–10 years of leadership experience managing enterprise data, analytics, AI, or business intelligence functions.
• Proven experience designing and implementing enterprise data warehouse, data lake, cloud data platform, and analytics solutions.
• Strong expertise in AI, Machine Learning, Predictive Analytics, Business Intelligence, Data Science, and enterprise reporting frameworks.
• Experience with data platforms such as Snowflake, Databricks, Hadoop, Teradata, Oracle, SQL Server, Azure Data Platform, AWS Data Services, or Google Cloud Data Platforms.