Igor Khrol
Head Of Data Engineering
Vilnius, Vilnius County, Lithuania
Summary
👤
Senior🎓
Top SchoolIgor Khrol is a Head of Data Engineering with 11 years of hands-on experience building reliable data platforms and QA-driven development practices for large-scale environments. Based in Vilnius, he leads Automattic’s data engineering group, owning ETL frameworks, a self-service SQL transformation platform, and the Hadoop-based Big Data cluster while championing CI/CD, static analysis, and quality gates. He brings deep technical fluency in Scala, Python, Spark, Trino, Airflow and cloud/container tooling, combined with a track record of shifting testing left and embedding quality across teams. A pragmatic people leader, he has moved teams to cost-optimized clouds and shortened feedback loops through tuned CI/CD and platform automation. Igor is also an active open-source contributor to flagship Apache projects like Airflow and Superset, where his work on SparkSubmitOperator impersonation, HDFS log handlers and Trino fixes improves production reliability for many users. His background in QA automation and training gives him a rare blend of test-first discipline and production-scale data engineering.
11 years of coding experience
7 years of employment as a software developer
Master Degree Computer Science, Master Degree Computer Science at Belarusian State UniversityMogilev Regional Liceum #3
English, Russian, Lithuanian, Russian
Stackoverflow
1,768reputation
183kreached
20answers
1question
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Github Skills (34)
apache-airflow10
trino10
spark10
data-pipelines10
selenium10
python10
back-end-development10
data-engineering10
workflow-engine10
sqlalchemy10
sql10
orchestration10
data-pipeline10
webdriver9
java9
Programming languages (10)
Github contributions (5)
apache/airflow
Aug 2019 - Sep 2025
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Data Engineer
Data EngineerContributions:8 reviews, 13 PRs, 43 comments in 6 years 1 month
Contributions summary:Igor primarily contributes to enhancements within the SparkSubmitOperator, introducing the ability to specify a proxy user for impersonation during Spark job submissions, as well as adding a `pool_pre_ping` configuration for the SQLAlchemy connection in the Airflow settings, to improve database connection handling. The user also addresses UI bugs related to DAG filtering and the display of tasks, specifically highlighting improvements in graph and tree views and ensuring correct JSON parsing. Further contributions focus on implementing the HdfsTaskHandler to allow storing task instance logs on HDFS.
airflowapache-airflowapachepythonscheduler
apache/superset
Jan 2023 - Mar 2026
Apache Superset is a Data Visualization and Data Exploration Platform
Role in this project:Back-end Developer
Back-end DeveloperContributions:6 reviews, 8 PRs, 7 comments in 3 years 1 month
Contributions summary:Igor primarily contributed to bug fixes and improvements within the Apache Superset backend. Their work involved addressing issues related to permissions, database interactions (specifically with Trino), and resolving 500 errors. They made modifications to core files including `superset/config.py`, `superset/views/sql_lab/views.py` and the trino database engine spec to resolve various issues. The user also corrected issues in test files.
apache-supersetdata-explorationdata-visualizationsupersetapache
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