Emil Ejbyfeldt
Staff Engineer at VML MAP
Malmo, Sweden
Summary
🤩
Rockstar🎓
Top SchoolEmil Ejbyfeldt is a Staff Engineer based in Malmö with five years of experience building and scaling backend and compute infrastructure for data-driven products. He has led compute infrastructure teams at LiveIntent and recently progressed to a Staff role at VML MAP, combining hands-on engineering with team leadership. Emil is an active open-source contributor to high-profile Apache projects—Airflow, DataFusion, and Spark—where he focuses on robustness, performance, and adding advanced SQL/aggregation capabilities. His background in Engineering Physics and a Master’s in Complex Adaptive Systems from Chalmers underpins a systems-oriented approach to complex distributed problems. Notably, he has a track record of fixing subtle correctness and serialization bugs and improving performance in widely used data platforms, reflecting both attention to detail and impact at scale.
5 years of coding experience
6 years of employment as a software developer
Master's degree Complex Adaptive Systems, Master's degree Complex Adaptive Systems at Chalmers University of TechnologyHong Kong University of Science and Technology (HKUST)
Github Skills (31)
apache-airflow10
spark10
data-pipelines10
python10
big-data10
data-serialization10
workflow-engine10
aggregate-functions10
arrow-keys10
java10
fusion10
serialization10
scala10
javas10
deserialization10
Programming languages (8)
Github contributions (5)
apache/datafusion
Jun 2024 - Nov 2024
Apache DataFusion SQL Query Engine
Role in this project:
Back-end Developer
Back-end DeveloperContributions:90 reviews, 33 PRs, 137 comments in 4 months
Contributions summary:Emil primarily contributed to the implementation and modification of aggregate functions within the Apache DataFusion query engine. They focused on adding new aggregate functions for linear regression and integrating these functions using UDAFs. The user also worked on fixing bugs and improving existing functionality, such as fixing the nullability of `array_agg`, correcting results for grouping sets, and addressing a panic in `VarianceGroupsAccumulator`. Additionally, the user improved code readability and documentation.
querypythonquery-enginedataframerust
apache/airflow
Jan 2021 - Feb 2024
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:Backend Engineer
Backend EngineerContributions:4 reviews, 5 PRs, 11 comments in 3 years 1 month
Contributions summary:Emil primarily contributed to bug fixes and improvements within the Apache Airflow codebase. They addressed issues related to type errors in the `monitor_pod` function and unchecked indexing in the `_build_metrics` function. Additionally, they worked on improving the graph view load time for DAGs with open groups, and re-enabled the clear action on the TaskInstanceModelView for the User role. They also unified the `aws_conn_id` type to always be `str | None` in several AWS-related operators.
monitorpythonschedulerapacheprogrammatically
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