Ege Elgun
Quantitative Research Engineer
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolEge Elgun is a Quantitative Research Engineer based in New York with nine years of software engineering experience building cloud-native storage and distributed systems. He has deep hands-on expertise from multiple roles at Databricks—designing serverless storage experiences, cloud-agnostic object storage, and improving DBFS tooling—and now applies that background to platform-level quant strategies at Citadel. Comfortable across Scala, Python, Spark, Hadoop and cloud storage APIs (S3, ADLSGen2, GCS), he has a track record of shipping robust backend features like large-file DBFS uploads, token lifecycle microservices, and deletion recovery. His early contributions include adding the official Wireshark NAN dissector and practical infrastructure work that spans billing/usage pipelines to storage lifecycle management. Colleagues know him for bridging low-level systems engineering with product-focused reliability, and for preferring pragmatic, well-tested changes that scale in production.
9 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at The University of EdinburghInternationa Baccalaureate Diploma Programme, Internationa Baccalaureate Diploma Programme at Nesibe Aydin Anatolian High Schools
English, Turkish
Stackoverflow
53reputation
2kreached
1answer
7questions
Github Skills (16)
file-handling10
python10
api-design10
command-line9
cli9
command-line-interface9
pytest8
versioning7
bot-framework6
ctypes6
actionlistener6
robotics6
opencv6
cmu-sphinx6
pathfinding6
Programming languages (7)
Github contributions (5)
databricks/databricks-cli
Feb 2021 - May 2022
(Legacy) Command Line Interface for Databricks
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 releases, 21 reviews, 21 commits in 1 year 2 months
Contributions summary:Ege primarily focused on enhancing the Databricks CLI's functionality, specifically improving the DBFS (Databricks File System) interactions. Key contributions include adding a `modification_time` field to the `FileInfo` object and refactoring the DBFS CLI's `put` method to support a new backend and handle large file uploads efficiently. Moreover, the user bumped the version number of the CLI in several commits. These changes improve the CLI's usability and efficiency for interacting with the Databricks platform.
command-line-interfacedatabrickscli
stormwindy/Qi-Table
Feb 2020 - Apr 2020
Contributions:11 PRs, 39 pushes, 6 branches in 1 month
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