Aseem Bansal is a software engineer with about 12 years of industry experience and eight years focused on data and ML using Python and SQL stacks. He has designed and implemented Snowflake-based data warehouses, productionized ML models (including Spark-based components), and driven data quality, observability, and security improvements at scale. Comfortable across JVM microservices and cloud-native tooling, he has a strong operational background with Terraform, Kubernetes, Airflow, and AWS/GCP services. He collaborates closely with data scientists and product teams to turn ad-hoc analyses into reliable pipelines and BI tooling like Apache Superset. An active contributor to the DataHub metadata project, he has made performance and ingestion improvements and clarified documentation around CLI and lineage. Experienced in distributed, remote teams since 2015, he combines hands-on implementation (often owning the majority of execution) with systems-level reliability thinking.
12 years of coding experience
8 years of employment as a software developer
Bachelor of Engineering (B.E.)/B.Tech. Electrical Electronics and Communications Engineering, Bachelor of Engineering (B.E.)/B.Tech. Electrical Electronics and Communications Engineering at Kurukshetra University
Data Analyst Nanodegree Data Analyst, Data Analyst Nanodegree Data Analyst at Udacity
Contributions:1 release, 979 reviews, 386 commits in 1 year 2 months
Contributions summary:Aseem primarily focused on bug fixes and enhancements to the datahub-project/datahub repository. They addressed issues in the command-line interface (CLI) related to response handling, particularly for deletion commands. The user also worked on documentation improvements, including re-arranging documentation related to scheduling, lineage, and CLI, adding examples for adding users. Additionally, the user implemented code changes related to performance testing and made code changes for improvements for ingestion performance.
Contributions:5 reviews, 12 PRs, 11 pushes in 1 year 7 months
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