Oct 2021 – Apr 2024 · 2 yrs 6 mos

• Founding member of CO Data engineering, built and maintained central warehouse that powers foundational datasets at Uber which are required for everyday analytics. Primarily responsible for ETLs that run across the Petabytle scale. Created and manages 70+ tier 1 and tier 2 datasets which have 10B + events and and serving >1M queries to internal customers/services.
• Optimized Tier 1 pipelines using HUDI/Spark to bring Freshness SLAs from 30+ hrs to ~ 3 hrs to power critical business decisions
• Worked closely with Machine Learning team, contributed to the development of robust features powering cutting-edge ML models powering recommendations for earner and suport automation. This collaboration has been instrumental in enhancing the precision and efficacy of Uber's predictive algorithms.
• Recognizing the value of time and resources, I've championed the implementation of data validation tooling, resulting in significant time savings exceeding 100+ hours for engineering teams. This initiative has not only streamlined workflows but also bolstered data integrity and accuracy.
• Defined the Data Engineering Interview guidelines and Hiring Competency Matrix for the Data Org to improve the candidate experience and also to ensure consistent evaluation is done. Chaired Bar raiser committee as well.
• Mentored and helped numerous engineers to quickly onboard to the Data Stack and to get familiar with the Uber infrastructure.

Dec 2019 – Oct 2021 · 1 yr 10 mos

• Real-time Queue Analytics:
• 1. Built flink service to process contact related events and dashboard which powers queue health metrics. This helped in meeting SLA for safety tickets (30 mins) so that business meets compliance in various geographies.
• 2. Built the serving layer for the real-time dashboard which is powered through Pinot for millisecond response time. Added observability metrics for the apis and flink service to ensure reliability and SLAs

Feb 2019 – Dec 2019 · 10 mos

• Built backfill utility for ETL pipelines which saved 50+ hours on a monthly basis
• Contributed to the Security design of the Core datasets as part of the Data big rocks initiative in 2019 to achieve GDPR compliance with minimal impact to 100+ downstream dependent customer pipelines.

Jul 2018 – Feb 2019 · 7 mos

Jan 2017 – Jul 2018 · 1 yr 6 mos

• . Working in Walmart Ad Exchange(WMX) team building data pipelines for Audience Targeting, Campaign Measurement.
• . Co-implemented propensity segment pipeline, which is machine learning based audience targeter worth millions dollars for Walmart.
• . Work in Progress: Get approximate estimate of audience size in real-time using datasketches.
• . Migrating data between cluster and changed logic & code when upstream data source/ infrastructure changed.

Jun 2016 – Dec 2016 · 6 mos

• I worked on analyzing logs
• (a) To detect when an application/data center goes down and alerting. I am able to do this in real-time.
• (b) To find the root cause why application died.
• Scale of Data : 1 Billion Messages / hour
• Technologies Used: Apache Hadoop, Java, Hive, ORC.

Jan 2015 – May 2016 · 1 yr 4 mos · Los Angeles

• I worked on DARPA funded projects. Most of them involve finding fraudulent activities on internet in various domains like Human Trafficking, Illegal weapons sale and counterfeit electronics. Work usually involved gathering information from different websites and entity linking them and finally visualizing the results.
• Technologies Used: Python, ElasticSearch, Apache Spark

Jul 2013 – Dec 2014 · 1 yr 5 mos · Hyderabad Area, India

• 1. Developed client side of web application in smartgwt framework using java, APIManagement - where API Service Providers can create proxy projects with different requirements like customized quota, data output, added security functionality and modify user permissions.
• Skills : Java, Smartgwt, Object Oriented Programming

Jan 2013 – Jun 2013 · 5 mos · Bengaluru Area, India

• 1. Developed a VBScript module that sends a daily email update to topline management about the Sales.
• 2. Developed sales dashboard used by Business Development teams.
• 3. Developed inventory planning dashboard that gives an estimate of required inventory based on the previous Sales and present pace of selling.