Ankit Surana · AVP Data Engineer at NatWest
I build the pipes the numbers arrive through.
Ten years of event-driven data platforms on AWS, now building agentic AI and retrieval systems on top of them. I care about the whole path, from the data model up to the button someone clicks.
Work
Each one has a write-up, so it stands on its own whether or not the source is public. Open repos link out as well.
Field notes
One real problem per post. What broke, why I did not see it coming, and what fixed it.
About
Ten years of making sure the numbers turn up on time.
I am Ankit Surana, an AVP and data engineer at NatWest in Bengaluru. Before that I spent close to eight years at Infosys, three and a half of them based in Edinburgh, ending as a technical lead. Most of my career has gone into event-driven pipelines on AWS. Kafka, Lambda, Glue, Redshift, Athena. The platform I work on carries north of and has to answer .
Lately that has meant agents. I was on the team that shipped a personalised spending assistant to customers, one of the first agentic AI features any bank put in front of the public, alongside a retrieval pipeline that reads the documents nobody wants to read. I hold an AWS Solutions Architect certificate and an MSc in AI and Machine Learning from Liverpool John Moores.
What I keep returning to is ownership. I would rather understand a system from the data model up to the button someone clicks than hold one slice of it very well. That is why I build things on my own time, and why none of them are finished.
What that added up to
- 80%less manual turnaround on insights covering roughly 500 million daily transactions, after rebuilding the pipeline end to end in Apache Airflow.
- <5sto answer a customer's question about their own transactions, by architecting agentic AI services across AWS, Azure AI and PostgreSQL.
- 88%accuracy classifying financial transactions, reached by working out which predictive parameters carried signal and dropping the rest.
- 40%off code management processing time across 50+ repositories, by automating the move from Bitbucket to GitLab. That one earned a Risk Hero Award.
- 30%faster queries through the Teradata to Redshift migration, because the reporting SQL was rewritten rather than lifted across unchanged.
- 20%more output from a team of ten analysts, after mentoring them and changing how the work was split.
On the record
Skills
The tools I reach for without thinking about it.
Languages
Streaming & big data
AWS
GenAI & agents
Machine learning
Data
Platform
On-device & backend
Let us talk about the hard part.
If you are hiring for something where owning the whole system is the job, or you just want to argue with a post, I read everything.
Usually replies within a day