Nov 2021 – Aug 2023 · 1 yr 9 mos · Bangalore Urban, Karnataka, India

• Built and led the product engineering organization responsible for customer-facing data products and ML-powered financial solutions for India's leading payments unicorn.
• Spearheaded the launch of real-time merchant analytics products that drove a 40%+ increase in merchant NPS through self-serve platform.
• Scaled the product engineering team from 15 to 40+ across full-stack, data, and ML engineering disciplines.
• Championed a successful cost optimization initiative, re-architecting infrastructure to reduce spend by 60% while simultaneously improving system performance.
• Developed a company-wide ML platform to power risk modeling and personalization, serving all core business units including Payment Gateway, Capital, and RazorpayX.

Jul 2018 – Nov 2021 · 3 yrs 4 mos · Bengaluru, Karnataka, India · On-site

• Leading engineering function for Data platform and Machine Learning Platform development comprising software engineers, data engineers, product managers, architects and analysts for India's biggest e-commerce.
• Building highly scalable and available platform to enable business, analytics, operations and data scientists teams by building capabilities to ingest, process, publish insights to help them take data driven decisions in near-real time and batch.
• Defining strategy and roadmap to manage all aspects of data through its life cycle Model development and deployment, training / retraining models, Schema definition and evolution, real-time streaming ingestion, realtime and batch processing, near-realtime and batch consumption (human or systemic), data lineage, compliance adherence, data quality monitoring and fixing, data security, analytics, backup and recovery, BCP, graceful degradation etc.
• Managing mission critical platform as all data driven business decisions especially cross functional in nature depends on this platform.
• Using primarily open source tech stack (Kafka, ES, HBase, Cassandra, Redis, Airflow, Aerospike, Spark streaming and batch, Flink, Kubeflow, Tenserflow, K8 etc)

Nov 2017 – Jun 2018 · 7 mos · Bengaluru, Karnataka, India

• India Head managing 60+ engineers across global offices (India, NY, Canada)
• Global practice lead for Data Architecture, Data Governance, and Big Data functions

Apr 2015 – Oct 2017 · 2 yrs 6 mos · Greater Bengaluru Area

• Responsible for building a data engineering organization from the ground up to enable business and product analytics through organization.
• Joined as the first member of the team, built a strong team of data engineers. Played dual role of data engineering leader for delivery and architecture. Built cross functional data products enabling 360 degree view of product and business analytics e.g. Order lifecycle, multi-channel user experience (msite, app, web), L0-L1 metrics, pricing engine, seller fraud detection.
• Lead the self-serve / data democratization charter which involved replacing manual processes of metrics generation / reporting with E2E automated refresh of dashboards, reports, cubes with data quality asserts.This significantly reduced human errors and time it used to take to provide metrics to business.
• Leading design and development of complex purpose built frameworks for enabling user insights on user interactions across platforms (app, website, msite) where data volume is more than 10TB a day.
• Driving Data Platform engineering, product strategy and roadmap to bring in customer focused platform features and making platform capabilities self-serve, scalable, easy to use.
• Established governance model and KPIs with users (analytics, business growth teams, data scientists, operational users, tech teams) and internal teams (tech, product) to set right processes for feature prioritisation, measuring platform adoption, defining and monitoring SLAs and user communication.

Mar 2009 – Mar 2015 · 6 yrs · Bangalore

• I was instrumental in setting up data practice up Bangalore, finding the right team and mentoring them as we transitioned from MPP to big data tech stack.
• Responsible for defining technology roadmap for data platform in terms of benchmarking and recommending right tech stack e.g. Hadoop distributions (comparing ORC vs Parquet, Impala vs Tez, Spark vs Tez etc).
• Playing the role of engineering manager also by leading teams across India and US to deliver analytical data products on big data platform.
• Designed real-time data collection/serving platform/AB test frameworks to personalize customer experience (on web/mobile) in real-time.
Responsible for providing architectural leadership for in house data (integration/matching/profiling) product development and leading engineering team through the development phase.
• Technology used: Hadoop, PIG, Hive, HCatalog, Cassandra, HBase, Storm, Kafka, Neo4J, Sqoop, Flume, Business Objects, Python, Netezza, Oracle, MySQL.

Sep 2007 – Mar 2009 · 1 yr 6 mos

• I was the only BI Specialist (Architect) where I used to work across multiple data projects as an architect and development lead.
• Designed geographically distributed risk management data warehouse using Microsoft tech stack.
• I was responsible for doing ETL design and data modelling for complex hierarchical source where data was required to be available for analysis within 5 minute of change.
• Designed Claims Enterprise data warehouse and SOAP data services layer on legacy mainframe based applications using data stage, DB2, WebSphere application server.
• Technology used: Datastage, DB2, MS SSIS, SSRS, Java, Business Objects, AS400.

Nov 2006 – Aug 2007 · 9 mos

• For Airtel India I was responsible for leading a team of 8 engineers to implement Teradata Telco LDM solution for India's biggest Telco carrier (Airtel, India).
• Key challenges involved (a) understanding existing business processes/data and mapping them with the LDM (b) data volume – Billion+ CDRs per day (c) solving for high concurrency on 80+ TB database Technology used: Teradata, Shell scripts, BTeQ, MLoad, Datastage, DB2, Business Objects.

Oct 1999 – Oct 2006 · 7 yrs

• I worked on multiple full lifecycle engagements in various parts of the world like US, UK, Australia, Hongkong, Dubai, Singapore etc Technology used: Teradata, DB2, Oracle, Shell scripts, Java, Python, BTeQ, MLoad, SAP ABAP, Datastage, Business Objects, ACTA, BO SDK, VB.