Lead - Data Platform & Engineering

About the Role:

We are seeking an experienced Lead - Data Platform & Engineering to own, manage, and modernize the Bank's enterprise data platform.

The role will be responsible for maintaining and enhancing the current data ecosystem while defining and executing the future-state data architecture roadmap. The individual will drive platform modernization, data engineering excellence, performance optimization, scalability, governance, and vendor management.

This is a strategic and hands-on leadership role requiring expertise in Data Warehousing, Data Engineering, Platform Operations, Architecture, and Transformation Initiatives.

Key Responsibilities:

Data Platform Ownership:

- Own and manage the Bank's enterprise data platform.

- Define and execute the Data Platform roadmap.

- Ensure platform stability, scalability, performance, and availability.

- Drive standardization and optimization across the data ecosystem.

- Manage platform lifecycle, upgrades, and technical debt.

Data Engineering & Integration:

- Lead design and management of enterprise data pipelines.

- Oversee data ingestion, transformation, and integration frameworks.

- Improve ETL/ELT efficiency and scalability.

- Support onboarding of new source systems and business requirements.

- Establish data engineering standards and best practices.

Data Warehouse & Analytics Platform:

- Manage Enterprise Data Warehouse (EDW) and associated data stores.

- Support business intelligence, reporting, analytics, and regulatory reporting requirements.

- Enable self-service analytics and downstream data consumption.

- Ensure platform readiness for AI/ML and advanced analytics initiatives.

Modernization & Architecture:

- Define future-state data architecture.

- Evaluate modernization opportunities and emerging technologies.

- Lead data platform transformation initiatives.

- Drive cloud, hybrid, lakehouse, data fabric, or modernization initiatives as appropriate.

- Support long-term architecture planning.

Platform Governance & Operations:

- Define operational standards and SLAs.

- Drive platform monitoring and performance management.

- Lead incident, release, change, and capacity management processes.

- Ensure documentation and operational readiness.

Regulatory & Compliance Support:

- Support regulatory reporting and audit requirements.

- Ensure data traceability and platform controls.

- Support data retention, archival, reconciliation, and compliance initiatives.

Vendor & Stakeholder Management:

- Manage platform vendors and implementation partners.

- Review solution designs and technical deliverables.

- Drive knowledge transfer and reduce vendor dependency.

- Work closely with Business, Technology, Risk, Compliance, and Operations teams.

Mandatory Experience:

- Ten to 15 years overall experience.

- Minimum 5 years in Data Platform, Data Engineering, Data Warehouse, or Data Architecture leadership roles.

- Experience managing enterprise-scale data platforms.

- Experience in Banking, BFSI, FinTech, or large enterprise environments.

- Experience supporting production-critical platforms.

Tech Stack:

- Enterprise Data Warehouse, Data Architecture, Data Modelling, Data Integration, ETL/ELT Frameworks, Data Lifecycle Management, SQL, Data Pipeline Development, Performance Optimization, Data Transformation, Production Support, Release Management, Incident Management, Capacity Planning, Platform Monitoring, Stakeholder Management, Vendor Management, Technology Governance, Team Leadership, Delivery Management.

Educational Qualification:

- B.E. / B.Tech., MCA, M.Tech., Master's Degree in Computer Science, Information Technology, Data Engineering, Analytics, or related disciplines.

- Relevant certifications in Data Engineering, Data Architecture, Data Warehousing, Cloud Data Platforms, or Enterprise Architecture will be an advantage.

What Success Looks Like:

- Establish ownership of the Bank's enterprise data platform.

- Define a 3-year Data Platform modernization roadmap.

- Improve platform performance, stability, and scalability.

- Deliver key modernization initiatives.

- Strengthen data engineering and data governance practices.

- Reduce vendor dependency through internal capability building.

- Enable future analytics and AI requirements through a scalable data platform.

Ideal Candidate:

- Own enterprise-scale data platforms.

- Drive platform modernization and transformation initiatives.

- Lead data engineering and architecture decisions.

- Manage vendors and implementation partners.

- Work effectively with business and technology stakeholders.

- Build a scalable, future-ready data ecosystem.