Shirshanka Das
Co-Founder And CTO at DataHub
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolShirshanka Das is a founder and CTO with 14+ years building large-scale data and distributed systems, currently leading Acryl Data (DataHub) to commercialize the open-source metadata platform he created. A UCLA Ph.D. and ex-LinkedIn principal staff engineer, he architected LinkedIn’s data and metadata strategy—leading GDPR, retention, deletion and a 150-engineer effort—and helped build core systems like Databus and Espresso. He combines deep backend engineering (contributions to Apache Gobblin and DataHub) with product instincts that have attracted major customers and $30M+ in funding. Comfortable moving from low-latency C++ services to Java/Scala big-data pipelines, he’s also an Apache committer and PPMC member influencing industry-grade integration tooling. Raised in Bihar with an early DIY computer curiosity, he pairs rigorous research training with a practical, developer-first approach to metadata problems. Outside work he keeps disciplined—swimming regularly—which mirrors his hands-on, operational focus in scaling data platforms.
14 years of coding experience
16 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)University of California, Los Angeles
Github Skills (16)
javas10
databases10
avro10
kafka10
schema10
python10
back-end-development10
data-integration10
java10
database10
data-engineering10
hadoop9
metadata9
json9
unit-testing8
Programming languages (5)
Github contributions (5)
datahub-project/datahub
Sep 2020 - Jan 2023
The Metadata Platform for your Data and AI Stack
Role in this project:
Back-end Developer
Back-end DeveloperContributions:32 releases, 2497 reviews, 940 commits in 2 years 4 months
Contributions summary:Shirshanka primarily focused on back-end development tasks, enhancing the functionality of the metadata ingestion pipeline. They added support for processing multiple MCEs in a single file, and fixed unit tests. Furthermore, they implemented code to support structured properties, and made improvements to database connection for the project's backend. They are responsible for adding column-level lineage.
data-managementdata-discoverydata-stackmodern-data-stackdata-catalog
apache/gobblin
Feb 2015 - Feb 2021
A distributed data integration framework that simplifies common aspects of big data integration such as data ingestion, replication, organization and lifecycle management for both streaming and batch data ecosystems.
Role in this project:Back-end Developer
Back-end DeveloperContributions:22 reviews, 59 commits, 90 PRs in 6 years
Contributions summary:Shirshanka primarily focused on enhancing the Gobblin data integration framework by implementing new features and improving existing ones. Their work includes adding support for Kafka writers, which involved creating and modifying Java files to integrate with Kafka schema registries, including the LiKafkaSchemaRegistry. Furthermore, the user made contributions to refactor and improve the codebase related to Hadoop file system helper classes and added a simple console writer.
datadcosdata-streambig-data-integrationbatch-data
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