The transition from a traditional banking environment to a global investment bank like Nomura is more than just a change in title—it is a shift in how one views the lifecycle and velocity of financial data.
My journey began with over a decade at Indian Overseas Bank (IOB), where I focused on the technical orchestration of credit and performance systems. Today, that foundation supports my work as a Data Engineer cum Software Engineer, building high-performance pipelines and open-source financial utilities.
The Foundation: 10 Years of Engineering at IOB
While many see banking through the lens of operations, I approached it as a massive, multi-dimensional data problem. My primary objective was to transform granular, branch-level data into high-velocity insights for two distinct audiences: Executive Leadership (Strategic) and Branch Managers (Tactical).
1. Multi-Period Performance Analytics Ecosystem
I architected a comprehensive monitoring system designed to track health across the entire bank hierarchy. The core of this system was a sophisticated data engine capable of automated Target-vs-Actual gap analysis.
To provide a 360-degree view of growth and volatility, I engineered pipelines to handle complex time-series aggregations, providing visibility across:
- Day-over-Day (DoD): Monitoring immediate business daily fluctuations.
- Month-over-Month (MoM): Identifying short-term growth trends and seasonal shifts.
- Quarter-over-Quarter (QoQ): Aligning performance with fiscal reporting cycles.
- Annual-over-Annual (YoY): Assessing long-term trajectory and structural growth.
2. Credit Analytics & Underwriting Pipelines
Beyond performance tracking, I specialized in the technical orchestration of MSME and Retail Credit workflows. This involved:
- Digital Underwriting: Translating legacy credit policies into automated, logic-driven decision engines.
- Risk Pipelines: Aggregating disparate data points into streamlined workflows to evaluate creditworthiness for retail portfolios and small businesses.
The Pivot: Macquarie and Nomura
In late 2024, my career moved into the global investment banking space. After serving at Macquarie, I transitioned to Nomura following their acquisition of the business.
In this high-stakes environment, the focus shifted toward high-frequency data and extreme reliability. My current role involves:
- Orchestrating high-scale financial data pipelines using Airflow.
- Managing containerized environments with Docker.
- Ensuring data integrity and performance using Java, Python, and PostgreSQL.
Bridging the Gap: Open Source Contributions
To contribute back to the fintech community, I maintain two key libraries on PyPI that reflect my focus on data reliability and financial logic:
- AtomSql: A lightweight Python ORM designed for clean and efficient database interactions, built with financial application performance in mind.
- qfinbox: A specialized fintech library focused on quantitative analysis and streamlining financial data workflows.
Looking Ahead
My goal for 2026 is to continue pushing the boundaries of what is possible at the intersection of systems engineering and finance. I am currently focusing on:
- AWS Certifications: Deepening my expertise in Data Engineering and Machine Learning on the cloud.
- Systems Languages: Mastering Go and Rust to build the next generation of high-performance financial architecture.