# Abhishek Andhavarapu > Staff Software Engineer @ LinkedIn | Building Scalable Distributed Systems Location: Milpitas, California, United States Profile: https://flows.cv/abhishekandhavarapu As a Staff Software Engineer at LinkedIn, I work on Espresso, a homegrown distributed online data store that handles tens of millions of queries per second and stores petabytes of data. Espresso is the primary data store for member and company profiles, messages, feed, and other core features of LinkedIn. I am responsible for designing, developing, and maintaining the core components and features of Espresso, ensuring its high performance, availability, and reliability. I am also the author of Learning Elasticsearch, a book that shows how to build highly scalable search applications using Elasticsearch, a popular open source search and analytics engine. I have over six years of experience in building analytics platforms based on Elasticsearch and other NoSQL technologies, such as MongoDB and Hadoop. I am a certified developer for Apache Hadoop and Microsoft .NET Framework 4, and have strong skills in Java, C#, and PHP. I am passionate about solving complex problems with distributed systems, scalability, and software design. I also contribute to open source projects and share my knowledge through my blog and GitHub. ## Work Experience ### Staff Software Engineer @ LinkedIn Jan 2018 – Present | San Francisco Bay Area Working on LinkedIn home grown distributed data store called Espresso. Espresso is LinkedIn’s horizontally scalable document store for primary data such as member and company profiles, InMail, social gestures (likes, comments, shares) various advertising data sets, etc. https://engineering.linkedin.com/teams/data/projects/espresso Led the architectural overhaul of the transport layer for Espresso. The new architecture can now scale 10X more to accommodate the growth of the platform and reduced query latency by 75%. Linkedin Engineering Blog https://www.linkedin.com/blog/engineering/infrastructure/solving-espresso-s-scalability-and-performance-challenges-to-sup Improved resilience and stability improvements of Espresso, a stateful, distributed database system, addressing issues such as single-host failure, client request storms and others By employing strategic enhancements, such as enabling follower reads, improving connection lifecycle management, implementing storage host failure resiliency, and introducing mechanisms to protect the system from request overloads, we achieved significant progress over the years. ### Author of book Learning Elasticsearch @ Packt Jan 2017 – Present | San Francisco Bay Area Packt : https://www.packtpub.com/big-data-and-business-intelligence/learning-elasticsearch Amazon : https://www.amazon.com/Learning-Elasticsearch-Abhishek-Andhavarapu-ebook/dp/B01MURNWEB This book will show you how to build highly scalable search applications using Elasticsearch. You can use Elasticsearch for a small application or a large application with billions of documents. It is built to scale horizontally and can handle both structured and unstructured data. You will install and setup Elasticsearch and Kibana, and handle documents using the Distributed Document Store. You will see how to query, search, and index your data, and perform aggregation-based analytics with ease. You will see how to use Kibana to explore and visualize your data. Furthermore, you will also learn to handle document relationships, work with geospatial data, and much more, with this easy-to- follow guide. Finally, you will see how you can set up and scale your Elasticsearch clusters in production environments. Packed with easy-to- follow examples, this book will ensure you will have a firm understanding of the basics of Elasticsearch and know how to utilize its capabilities efficiently. ### Senior Software Engineer @ eBay Jan 2015 – Jan 2018 | San Francisco Bay Area Currently working on the next generation Order Search over billions of orders using Elasticsearch, Kafka, Storm which will enable text search and complex filtering on orders. Huge performance gain will help millions of users using eBay. ### Senior Data Engineer (Previously Allegiance, Inc) @ MaritzCX Jan 2015 – Jan 2015 • Redesigned the existing ETL pipelines (Hadoop, Hive) with Apache Spark on Yarn and HBase. • Improved the speeds of the ETL pipelines by 50X. • Distributed percolator to create alerts on streaming data. - Hadoop, Hive, Elasticsearch, RabbitMQ. ### Software Engineer @ Allegiance (Now MaritzCX) Jan 2012 – Jan 2015 • Awarded “Employee of year 2013” for my contributions in design and development of big data platform. • Experience in architecting the reporting platform based on SQL in to NoSQL using ElasticSearch. Improved speeds 100X and highly scalable. • Developed an API to talk to Elasticsearch. • Designed and developed the etl process to push the data from SQL to HADOOP and from HADOOP to Elasticsearch. • Designed Spotlight Data Mining (http://www.allegiance.com/products/spotlight). Spotlight mines millions of records of data to uncover patterns of significance and value in real time. • Implemented a queue based execution plan for Spotlight to take advantage of all the nodes in the farm. • Worked on UBER Reporting framework. UBER Framework allows large scale analytical queries on unstructured data. ### Software Engineer @ Utah State University Jan 2010 – Jan 2012 | Logan, UT Public Health Master Patient Index (phMPI), funded by Utah Dept. of Health The phMPI is a service-oriented distributed system that integrates public health data from various sources within Utah Dept. of Health (Intermountain Healthcare, UDOH, UOU). • Design, code and test distributed systems • Implemented API’s for the phMPI. • Developed publication services that allow data consumers to subscribe to and automatically receive certain kinds of data from the phMPI when that such data is added, changed or deleted. • Tested service components (NUnit). ### Java Programmer @ Utah State University Jan 2010 – Jan 2011 Developed Java Applets using Swing for graphical representation of data structures (Splay Trees, Binomial heaps, Binomial Queues, Recursive and Greedy Coin Change, Tetris) as a learning aid for college and high school students. Improved the usability of existing applets by enhancing the User Interface. ### Software Design Engineer, Intern @ Pragam Inc Jan 2007 – Jan 2007 Designed the ASP.NET interface for Student Attendance Management System (SAMS). Improved the usability of the exiting ASP.NET pages. ## Education ### MS in Computer Science Utah State University ### BE in Electronics and communication Andhra University ## Contact & Social - LinkedIn: https://linkedin.com/in/abhishek376 - Portfolio: http://abhishek376.wordpress.com --- Source: https://flows.cv/abhishekandhavarapu JSON Resume: https://flows.cv/abhishekandhavarapu/resume.json Last updated: 2026-04-12