Sandor Murakozi
Head Of Engineering at boam
Budapest, Hungary
Summary
👤
Senior🎓
Top SchoolSandor Murakozi is a seasoned engineering leader based in Budapest with over two decades of Java experience and 16 years in Scala, currently serving as Head of Engineering at boam. He has managed teams of up to 25 developers and progressed through technical and managerial roles at companies including Cloudera, MSCI, and Feastfox. Sandor combines hands-on backend and QA skills—evidenced by contributions to Apache Spark that improved streaming UI behavior and test coverage—with strategic leadership in product-focused engineering organizations. He has a track record of moving between individual contributor and management paths, which helps him retain strong technical credibility while scaling teams. His background spans enterprise data platforms and real-time streaming systems, and he brings a practical blend of architecture, quality engineering, and people management to delivery. Trained in computer science and economics, he is comfortable navigating both technical trade-offs and business priorities.
8 years of coding experience
21 years of employment as a software developer
Bachelor's degree, Computer Science and economics, Bachelor's degree, Computer Science and economics at Szegedi Tudományegyetem
Hungarian, English
Stackoverflow
4,382reputation
245kreached
37answers
7questions
scala
top-5%
oop
top-5%
Github Skills (20)
spark10
testing10
big-data10
java10
scala10
javas10
oop9
ui-design7
front-end-development7
uid7
inputstream6
design-patterns6
casting6
functional-programming6
case-class6
Programming languages (2)
Github contributions (5)
apache/spark
Nov 2017 - Dec 2018
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer & QA Engineer
Back-end Developer & QA EngineerContributions:8 PRs, 82 comments in 1 year 1 month
Contributions summary:Sandor primarily contributed to the Apache Spark codebase by addressing bugs and improving the UI of the Spark application. Specifically, the user fixed issues related to incorrect job descriptions and UI unaccessibility in long-running streaming applications. Additionally, the user was involved in refactoring code to utilize public API types for application representation, as well as converting ML tests for structured streaming, demonstrating expertise in testing and improving the overall quality of the Spark project.
analyticspythondata-processingsqlapache
smurakozi/spark
Nov 2017 - Apr 2018
Mirror of Apache Spark
Contributions:30 pushes, 9 branches in 4 months
spark-mlapachebig-datasparkscala
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