Data & AI engineering for regulated finance

About

I'm Prashant Singh, a data and AI engineer in Gurugram. I have spent my whole career inside regulated finance: twelve years across a public-sector bank and two global asset managers.

I started at Indian Overseas Bank in 2014 as a Python developer and stayed ten years, finishing as a Senior Data Engineer and Manager. That is where I learned the job end to end, from analytics and modeling to the warehouse underneath them, and by the end I was leading a six-member engineering team.

At Macquarie Asset Management I moved to the buy side, building investment data pipelines on PySpark, AWS, and Airflow. Since December 2025 I have been a Lead Software Engineer at Nomura Asset Management, working on data products and pipelines.

Separately from my employment, I build in public on my own time, with public data: six Python packages on PyPI and the writing on this site, where most posts come with code you can run.

Views on this site are my own and do not represent any current or former employer. Nothing here describes or contains an employer's systems, code, or data.

How I work

  1. 01

    Make the error path explicit.

    TRY…CATCH, a visible ROLLBACK, and a THROW form a contract any reviewer can read. Implicit safety nets stay underneath, not instead. the post →

  2. 02

    Put a task boundary where you would stop and inspect the data.

    Or where you would want a restart to begin, and nowhere else. One 300-line task is undebuggable; a task per pandas call is unreadable. the post →

  3. 03

    Configuration, until it becomes a worse programming language.

    Spec-driven pipelines are the right instinct. Once the spec grows conditionals, the line between metadata and code has been crossed. the post →

  4. 04

    One scheduler, not a scheduler inside the scheduler.

    Spec-driven DAG factories keep jobs as config without giving up per-job scheduling, backfills, and observability. the post →

  5. 05

    Never trust one metric.

    Pair a statistical metric with the business number the bank will feel, computed out of time. Trust neither in isolation. the post →

Career

  1. Nomura Asset Management International

    Dec 2025 — Present

    Lead Software Engineer

    Data products and pipelines for fund operations with Python, Apache Airflow, SQL Server on AWS, and FastAPI, on Snowflake and Databricks.

  2. Macquarie Asset Management

    Oct 2024 — Dec 2025

    Senior Data Engineer, Assistant Manager

    Investment data pipelines with PySpark, AWS, and Apache Airflow, including migration of legacy batch scheduling to Airflow.

  3. Indian Overseas Bank

    Jun 2014 — Oct 2024

    Python Developer → Senior Data Engineer, Manager

    Data engineering and analytics across lending, risk, and compliance; led a six-member engineering team.

Certifications

Courses

Education

Publication

“Incremental Associative Memory Model Algorithm for Highly Scalable Recommender Systems”

International Journal of Computer Applications (IJCA), vol. 68 · Apr 2013 · DOI ↗

Elsewhere

github
github.com/prashant-fintech
linkedin
linkedin.com/in/prashant-fintech
email
prashant@singhprashant.in
pypi
six packages
rss
singhprashant.in/feed.xml

For a role, a data-platform problem, or a question about something I wrote, the contact form goes straight to my inbox.