Hiring profile

Senior Backend Engineer

I build reliable backend and data systems where architecture, migration, production operation, and recovery all matter.

13+ years · About five years owning production data infrastructure · India-based · remote worldwide

Hiring thesis

I work best on ambiguous backend problems that need architecture ownership, safe migrations, production responsibility, and measurable product outcomes.

Relevant role fit: Senior Software Engineer — Backend · Senior Platform Engineer · Senior Data Platform Engineer · Senior Data Infrastructure Engineer · Founding Engineer

Production proof

Ownership · system · scale

Data platform

I owned the rebuild of customer and order data infrastructure serving 200+ merchants across five commerce platforms across five commerce platforms. Webhook freshness moved from days-late batch data to sub-minute.

Days → sub-minute webhook freshness

Ownership · product · adoption

Recommendation system

I initiated and built a three-tier recommendation product, from trust-first manual blocks to live ranking across five regions.

80%+ of merchants who trialled Smart tier adopted it

Ownership · data product · rollout

Customer segmentation

I owned the query model and builder that unified four source systems for Customer Success teams.

1,000+ active segments within six months of launch

Selected work · recommended reading order

Start with the data platform, then read the production incident. These show architecture ownership and operational judgment fastest.

Primary case study · recommended first read

The data platform

I owned architecture, migration, and rollout for customer and order data across 200+ merchants on five commerce platforms. Freshness moved from days-late batch data to sub-minute webhook freshness.

days → sub-minute3-month migration200+ merchants

Product system · recommendations

Recommendation blocks

I owned the trust ladder, serving system, and adoption measurement for a recommendation product built from zero.

80%+ trial adoption5 regions200ms p99

Customer data product · self-serve

Customer segmentation

I owned the query model, builder, and production operation that turned four source systems into self-serve audience creation.

4 source systems1,000+ active segmentsminutes not days

Production incident · technical deep dive

I stopped a production migration when a 50M-row CDC snapshot began blocking writes.

Debezium consumed 60% CPU. I stopped the snapshot, used the existing Datastream path to recover, and changed the rollout strategy.

Read the incident and recovery decisions →

Incident record · ten hard problems

A decade of production lessons: query shape, lock contention, silent data failure, memory pressure, database constraints, resilience patterns, and the judgment to trade freshness for stability when the system needs it.