Hyderabad, Telangana, India
I build and lead the data-intensive systems behind financial reporting, revenue recognition, and risk. I came to management the long way — through nearly a decade as an engineer on some of the hardest-scale problems at Meta, Amazon, and Flipkart — which is why I lead technical teams on the merits, not just the org chart. I operate with high agency, and I build teams that do the same — people who take ownership, move without waiting for permission, and treat constraints as problems to solve. The teams I'm proudest of share five things: • An ambitious charter worth caring about • A clear technical vision and strategy • On-time delivery without sacrificing quality • A manageable operational burden • Motivated individuals who are visibly growing Across 13+ years and four years at Stripe, I've grown from tech lead to managing two teams (~15 engineers) powering Revenue Recognition and financial reporting — rebuilding a team through attrition and escalations into a reliable, high-velocity one, shipping connectors featured at Stripe Sessions and many more impactful ships. Before that I built Meta's metric-definition model for Ads experimentation (co-inventing a filed patent) and launched Secure Delivery at Amazon — a ground-up, handling ~400K requests/min. I'm a collaborative leader with a first-team mindset, happiest building durable systems and the high-ownership, low-drama teams behind them. I'm open to engineering leadership roles, if you're building something interesting and high-stakes, let's talk.
• Leading two teams, Accounting Foundations and Financial Reporting (~15 engineers across both), powering Stripe's Revenue Recognition and financial-reporting products. • Accounting Foundations owns the data infrastructure, integrations, and standardized data contracts the Revenue Recognition product is built on; Financial Reporting delivers the reports customers rely on for accounting and revenue tracking. • Helping define and continuously improve the org-wide ops-review format, AWS cost DRI for the org.
• Inherited a team hit by high attrition and operational escalations; rebuilt it through hiring and development into a reliable team shipping at strong velocity. • Ran a quarter-long reliability lockdown that improved observability and cut operational load. • Delivered org-level reporting, report-freshness improvements, fee-transparency reports, and reporting UX upgrades (refreshed layout, drill-down for auditability) — including a contact-rate reduction worth ~$500K in annual support-cost savings.
• Managed a team of 8 engineers (grown from 6), expanding its charter from data ingestion to data export for large customers. • Launched Apple and Google Play connectors for Revenue Recognition — featured at Stripe Sessions 2024. • Shipped S3 and GCP data destinations for the Stripe Data Pipeline — announced on the 2024 NY tour. • Mentored and Grew engineers through direct coaching.
• Co-inventor on a filed Meta patent application for a DSL-based, ML-driven configurable measurement platform for ads/content experimentation - https://patents.google.com/patent/US20230316325A1 • Built the initial (0→1) separated metric-definition model for Meta's measurement platform, and helped define and validate new feature-framework capabilities essential for Ads experimentation. • Cut dev setup time for the Raw Events pipeline from ~1 week to 3–4 hours by automating the full setup — eliminating a recurring class of oncall requests. • Extended a large legacy events pipeline to compute new Basic Ads metrics (~40 metrics) on additional data sources with full backward compatibility, and drove a cleanup coordinating partition removal across 19 downstream teams.
• Led the ground-up launch of Secure Delivery (delivery-time OTP) for high-risk transactions in the US — drove it single-handedly across 5–6 teams, designing a line-item-level fan-out risk evaluation handling ~400K requests/min (~10× order throughput), The line-item granularity resolved a Bezos-escalation; previously a low-value item could trigger an unnecessary OTP challenge when basketed with a high-value one. • Simplified false-positive-rate (FPR) experimentation for risk scientists by adding a new platform-config stage — cut experiment setup from 3–4 days to ~1 day, and by making measurement easy to run, helped drive a ~30% reduction in overall FPR over the following six months. • Built N-way champion/challenger experimentation into the risk platform (integrated with Amazon Weblab), letting scientists A/B test evaluation configs generically; shipped a CLI that cut config-push time from 3 days to 1 day. • Shipped repeatedly across marketplaces — Appstore Abuse Evaluation (US & UK), Secure Delivery (US), JP Abuse Evaluation — while mentoring new hires, juniors and interns and being a go-to for tough operational/oncall issues.
Part of early engineering team from 0 to 1 journey to launch and scale the product to disburse more than 2000+ loans monthly and ecosystem around it - app capabilities, flexible EMIs(FMI) modelling, gamification, Collection Platform, Data Collection Platform, Decision evaluation platform etc.,
• Architected and Launched the first ever PLA(Product Listing Ads aka Shopping Ads) for Flipkart using Google Merchant Center(GMC) by intelligent mapping of flipkart catalog to google shopping hierarchy. Scaled and created a realtime system that syncs the availability and pricing between internal catalog with ads. • Launched Experimentation platform for optimising bids to save budget. Built models using ML techniques (logistic regression, KNN etc..) trained on performance data to estimate bids for a Ad position. • Engineered seamless integrations between internal events and external platforms (Google, Facebook, Vizury etc.)