Milan Dankovic
Software Engineer at Databricks
Belgrade, Central Serbia
Summary
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Rockstar🎓
Top SchoolMilan Dankovic is a Software Engineer at Databricks with two years of hands-on experience building and optimizing back-end systems and data processing features. He has contributed to Apache Spark SQL—improving error diagnostics and adding collation-aware string functions—demonstrating comfort with large, widely used open-source codebases. Milan’s background spans productionizing research at Bending Spoons, an internship on experimental Teams features at Microsoft, and teaching core CS courses at the University of Belgrade, reflecting both practical and pedagogical strengths. Currently pursuing a master’s in Computer Science and Engineering at Politecnico di Milano, he blends strong academic foundations with real-world engineering. Colleagues would describe him as curious, detail-oriented, and adept at turning complex algorithmic work into reliable, maintainable systems.
2 years of coding experience
1 year of employment as a software developer
Master's degree Computer Science and Engineering, Master's degree Computer Science and Engineering at Politecnico di MilanoBachelor's degree Computer Software Engineering, Bachelor's degree Computer Software Engineering at University of Belgrade, School of Electrical EngineeringGrammar School "Bora Stankovic" Nis
English, Serbian
Github Skills (7)
testing10
spark10
sql10
scala10
java9
javas9
big-data9
Programming languages (1)
Github contributions (3)
apache/spark
Mar 2024 - Mar 2025
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:232 reviews, 28 PRs, 255 comments in 1 year
Contributions summary:Milan primarily focused on enhancing the Apache Spark SQL engine. Their contributions involved assigning names to error classes, modifying tests to reflect these changes, and improving error messages. They also added collation support for string functions like `REPEAT`, `INSTR`, `FIND_IN_SET`, `REPLACE`, `LOCATE` and `SUBSTRING_INDEX`, by implementing new logic and generating appropriate code for different collation types. They also worked on adding support for the `TRANSLATE` function.
analyticspythondata-processingsqlapache
miland-db/spark
Mar 2024 - Feb 2025
Apache Spark - A unified analytics engine for large-scale data processing
Contributions:4 PRs, 325 pushes, 29 branches in 11 months
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