Pankaj Koti is a data platform engineer with 8 years of experience building and scaling production-grade systems in Python and distributed environments. Currently an Open Source Engineer at Astronomer and an Apache Airflow committer, he contributes integrations that bridge Airflow with GCP and Databricks, including deferrable operators and example DAGs that help teams adopt cloud data workflows. His background spans startups and large tech firms—founding technical teams at AgroStar and engineering roles at Zalando, OLX, and LightBeam—giving him a mix of product-minded engineering and operational rigor. He holds Nanodegrees in Data Engineering and Data Streaming and applies streaming and batch patterns to real-world pipelines. Based in Pune, India, he combines hands-on coding with community leadership in one of the most widely used workflow platforms, making him effective at both implementing and evangelizing robust data infrastructure. An under-the-radar strength is his knack for turning open-source contributions into practical, production-ready components that reduce cloud integration friction for teams.
8 years of coding experience
8 years of employment as a software developer
Data Engineering Nanodegree, Data Engineering Nanodegree at Udacity
Bachelor of Technology - BTech Computer Science and Engineering, Bachelor of Technology - BTech Computer Science and Engineering at Walchand College of Engineering
Class 10+2 Computer Science, Class 10+2 Computer Science at Maharashtra Board
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Data Engineer
Contributions:744 reviews, 133 PRs, 41 pushes in 3 years
Contributions summary:Pankaj contributed to the implementation of example DAGs, sensors, and operators within the Google Cloud Platform (GCP) ecosystem, specifically focusing on leveraging Google Cloud Storage (GCS) and Dataproc for data processing. These contributions included adding example DAGs that demonstrate usage of GCS sensors, creating a deferrable capability for the DataprocDeleteClusterOperator, and adding the `DatabricksNotebookOperator`. The user's work enhances the capabilities of Apache Airflow by integrating it with various GCP services and Databricks, demonstrating their proficiency in building data pipelines.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Contributions:10 pushes in 1 month
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.