Prakhar Jain is a data engineer with 11 years’ experience specializing in high-performance distributed systems and large-scale Spark pipelines, currently working at UBS after a recent role building big data solutions at Credit Suisse. He combines a precision-first mindset honed in the financial domain with hands-on expertise in Java, Spark, SQL and Databricks to make data faster, more reliable, and business-ready. An active open-source contributor, Prakhar has improved core Apache Spark internals (SQL and Core) and enhanced Delta Lake’s transaction and logging features, demonstrating real impact on widely used data platforms. He prizes creative problem-solving over clever hacks, balancing deep technical rigor with a user-centric approach to delivering production-grade systems. Outside work he channels the same curiosity into reading, badminton, and long weekend rides—fuel for pragmatic, resilient engineering.
11 years of coding experience
3 years of employment as a software developer
DBDA, Big Data Analytics, A, DBDA, Big Data Analytics, A at SunBeam Institute of Information Technology, Pune-Karad
Bachelor of Technology - BTech, Computer Science, A, Bachelor of Technology - BTech, Computer Science, A at Dr. Ram Manohar Lohia Awadh University, Faizabad
XII, XII at St. Joseph's School, Shaktinagar, U.P.
Class X, Class X at St. Joseph's Convent High School, Robertsganj
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Role in this project:
Back-end Developer
Contributions:341 reviews, 52 commits, 42 PRs in 1 year 8 months
Contributions summary:Prakhar Jain contributed to the core functionalities of the delta-io/delta project by implementing and refactoring features related to transaction commit statistics and logging. Their work included adding usage logs for the `DeltaCommand.commitLarge` code flow, refactoring commit statistics for better insights, and refactoring the conflict detection code flow for improved readability and efficiency. Additionally, they introduced new test suites, refactored configuration-related code, and enhanced existing tests, improving the overall stability and monitoring capabilities of the Delta Lake project.
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Contributions:24 reviews, 1 commit, 15 PRs in 1 day
Contributions summary:Prakhar's commits primarily focus on enhancing the Apache Spark codebase, specifically in the SQL and Core modules. Their contributions involve implementing batching support for partition management, improving block replication mechanisms, and addressing executor decommissioning processes to gracefully handle cached data. They also improved canonicalization of query plans, avoiding unnecessary sort/exchange nodes in query execution. These changes demonstrate expertise in optimizing data processing and improving the efficiency of the Spark engine.
analyticspythondata-processingsqlapache
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