Andrey Anshin
Tbilisi, Georgia
Summary
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RockstarAndrey Anshin is a data engineer with nine years of experience building reliable ETL pipelines and data platforms across finance and enterprise software, currently based in Tbilisi, Georgia. He’s known for an almost obsessive focus on data quality and resilient data processes, a trait reflected in his role as an Apache Airflow committer and PMC contributor working on core dag-processor internals. Andrey has progressed from reporting and ETL roles in banking to senior and lead engineering positions, delivering backend and DevOps improvements that reduce redundancy and harden workflow execution. He brings practical experience with AWS integrations and workflow orchestration at scale, and his contributions to the widely used Apache Airflow project highlight his impact on production-grade orchestration. Less obvious: his career shows a steady shift from analyst-heavy roles into infrastructure-facing engineering, combining domain knowledge of financial data with low-level system fixes that prevent subtle production failures.
9 years of coding experience
13 years of employment as a software developer
Stackoverflow
321reputation
14kreached
22answers
0questions
Github Skills (14)
aws10
python10
devops9
bash8
debugging8
cloud-computing8
testing7
connections6
cron6
docker6
airflow6
sqlalchemy6
type-error6
flask6
Programming languages (8)
Github contributions (5)
apache/airflow
Sep 2021 - Jun 2024
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Backend & DevOps Engineer
Backend & DevOps EngineerContributions:2274 reviews, 942 PRs, 396 pushes in 2 years 9 months
Contributions summary:Andrey primarily worked on tasks related to the internal workings of the "dag-processor" command within the "airflow" repository, focusing on optimizing and fixing configuration fetching and service setup. Their contributions included removing redundancy, modifying process group management for the "DagFileProcessorManager," and dropping support for Python 3.6 compatibility. They also addressed a bug in how the StepFunctionHook handles region names and contributed to the AWS-related documentation.
monitorpythonschedulerapacheprogrammatically
Taragolis/airflow
Sep 2021 - Jun 2024
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Contributions:992 pushes, 982 branches in 2 years 9 months
monitorapacheprogrammaticallyapache-airflowairflow
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