Lead - Data Platform and Decision Engineering

To own and drive the organizations enterprise data ecosystem and decisioning capabilities. The role will act as the bridge between business, analytics and technology teams, enabling scalable data architecture, advanced analytics platforms, and intelligent decision systems that support business growth. The incumbent will own end-to-end enterprise data architecture including data ingestion, transformation pipelines, enterprise data warehouse, analytical models, and data governance frameworks while supporting business decision-making through scalable and optimized platforms. Educational Qualification B.E./B.Tech in Computer Science / Information Technology / Electronics or equivalent M.Tech / MBA / Post-Graduation in Analytics or related field will be an added advantage Experience Requirements Minimum 7 years of experience; ideal candidate with 12 years Minimum 3 years of hands-on ownership of enterprise data platforms Strong experience in: Enterprise Data Warehouse (EDW) Data pipelines and analytics platforms Performance optimization Vendor management Data governance frameworks Technical Expertise Data Platform Enterprise Data Warehouse architecture Dimensional modelling Data marts Metadata management Data lineage management Oracle Ecosystem Strong working experience in: Oracle Autonomous Data Warehouse (ADW) Oracle Analytics Cloud (OAC) PL/SQL SQL optimization and query tuning Partitioning Performance optimization Integration & Engineering API integrations Data ingestion frameworks Batch and near real-time processing Data transformation pipelines Feature engineering pipelines Analytics & Decision Enablement Analytical datasets Data products Model deployment enablement Decision engine implementation Governance & Security Data quality controls Data access management Auditability and compliance frameworks Data reconciliation and lineage Key Responsibilities A. Platform Ownership Own and manage end-to-end enterprise data architecture including: Source systems Data ingestion Transformation pipelines Enterprise warehouse Semantic models Analytical data marts B. Oracle Ecosystem Leadership Lead and optimize Oracle ADW and OAC environments Drive SQL tuning, capacity planning, workload optimization, and platform performance improvements Reduce vendor dependency through internal capability building C. Data Engineering Design and operationalize: Batch pipelines Near real-time pipelines Feature engineering pipelines Reusable analytical datasets D. Decision Engineering Build and operationalize platforms supporting: Credit models Collections models Customer propensity models Fraud models Integrate model outputs into business applications including: LOS LMS CRM Other enterprise applications E. Governance Own and establish: Data quality controls Data lineage Metric consistency Audit readiness Data reconciliation frameworks F. Stakeholder Management Partner with business teams, technology teams, vendors, and leadership stakeholders Drive cross-functional collaboration for successful execution of data initiatives Desired Competencies Strong analytical and problem-solving ability Strategic thinking and decision-making capability Strong stakeholder and vendor management skills Leadership and team management capability Excellent communication and collaboration skills Preferred Experience BFSI / NBFC / Microfinance domain experience preferred Experience in credit, collections, fraud analytics, and customer decision systems preferred Exposure to AI/ML enablement platforms will be an added advantage To own and drive the organizations enterprise data ecosystem and decisioning capabilities. The role will act as the bridge between business, analytics and technology teams, enabling scalable data architecture, advanced analytics platforms, and intelligent decision systems that support business growth. The incumbent will own end-to-end enterprise data architecture including data ingestion, transformation pipelines, enterprise data warehouse, analytical models, and data governance frameworks while supporting business decision-making through scalable and optimized platforms. Educational Qualification B.E./B.Tech in Computer Science / Information Technology / Electronics or equivalent M.Tech / MBA / Post-Graduation in Analytics or related field will be an added advantage Experience Requirements Minimum 7 years of experience; ideal candidate with 12 years Minimum 3 years of hands-on ownership of enterprise data platforms Strong experience in: Enterprise Data Warehouse (EDW) Data pipelines and analytics platforms Performance optimization Vendor management Data governance frameworks Technical Expertise Data Platform Enterprise Data Warehouse architecture Dimensional modelling Data marts Metadata management Data lineage management Oracle Ecosystem Strong working experience in: Oracle Autonomous Data Warehouse (ADW) Oracle Analytics Cloud (OAC) PL/SQL SQL optimiza