Pooja S Raj

Led the end-to-end product lifecycle for Gen BI, an AI-driven BI platform consolidating all datasets into a unified data mart refreshed daily via DDL + Airflow, enabling real-time insights and faster decision-making. Defined the roadmap for natural-language querying, RAG-based insight generation, multimodal AI, and unified access to inventory, backlog, aging, and purchase data — reducing decision latency through automated insights and follow-up query generation. Directed cross-functional delivery across UI, API, and analytics teams to build a logistics analytics platform adopted by 3+ business units, improving shipment visibility and operational reporting. Delivered self-service analytics through Power BI dashboards, SSAS cubes, and ThoughtSpot integrations; defined product KPIs and monitored adoption, performance, and user satisfaction post-release. Led Agile ceremonies (sprint planning, backlog grooming, stakeholder alignment) for a 12-member cross-functional team; translated complex business requirements into clear user stories, acceptance criteria, and prioritization frameworks. Extended delivery into AI-first practices — designed agentic workflows and SOPs (using Windsurf) that automate BRD creation, wireframes, UI, and APIs, using ATLAS analytics personas as the reference implementation to scale delivery quality and speed. Spearheaded automation using Automation Anywhere and Python, delivering 3–4% cost savings (~$22M) and ~49 monthly hours saved. Recognized as two-time Innovation Olympics winner; recipient of Game Changer and Winning Together awards.

Developed and optimized SSIS packages and T-SQL stored procedures for high-volume banking data workflows. Partnered with business teams to gather reporting requirements and deliver actionable BI reports using SSRS. Improved data pipeline efficiency and SQL performance, contributing to robust and timely reporting.

Contributed to Finacle Core Banking implementations for major banks including IOB (India) and Sampath Bank (Sri Lanka). Developed PL/SQL procedures, resolved performance bottlenecks, and handled technical escalations during large-scale migrations.