Pavan Sharma
Principal Software Engineer at Uniphore
Bengaluru, Karnataka, India
Summary
👤
Senior🎓
Top SchoolPavan Sharma is a Principal Software Engineer based in Bengaluru with 10 years of experience building backend and DevOps solutions for data and workflow platforms. He has progressed through senior engineering roles at Gainsight and Infoworks.io and now drives platform work at Uniphore, focusing on reliable, scalable systems. A Java specialist by background, Pavan contributes to high-profile open-source projects like Apache Airflow, where he’s fixed race conditions, KubernetesExecutor issues, and improved SQLAlchemy/session handling. He blends hands-on bug fixes with architectural improvements, comfortable both in daemon/process-level concerns and cloud-native executor behavior. Colleagues describe him as pragmatic—able to untangle subtle concurrency and orchestration problems that often hide in production. His electronics-and-communications engineering foundation gives him a systems-minded approach to software design and operations.
10 years of coding experience
8 years of employment as a software developer
High School, Science, A, High School, Science, A at N K High-school,PetladEngineer’s Degree, Electronics & Communication, First Class, Engineer’s Degree, Electronics & Communication, First Class at Ipcowala Institute Of Enginnering & Technology,Dharmaj
English, Hindi, Gujarati, haryanvi
Github Skills (21)
kubernetes10
develop10
data-pipelines10
python10
data-engineering10
workflow-engine10
airflow10
kubernetes-pods10
orchestration10
orchestra10
backend10
data-pipeline10
devops10
apache9
celery9
Programming languages (2)
Github contributions (5)
apache/airflow
Oct 2022 - Nov 2024
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:14 reviews, 14 PRs, 25 comments in 2 years 1 month
Contributions summary:Pavan contributed to the Apache Airflow project by addressing race conditions in trigger assignments, adding new file processing functionalities, and fixing issues related to daemon mode and metrics. They also removed a PID argument from a Celery option and added support for additional SQL Alchemy session arguments. Furthermore, the user worked on fixing issues related to KubernetesExecutor and resolved a problem with terminating the Kubernetes watch in case of unknown errors.
monitorpythonschedulerapacheprogrammatically
pavansharma36/airflow
Oct 2022 - Nov 2024
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Contributions:88 pushes, 5 branches in 2 years 1 month
monitorapacheprogrammaticallyapache-airflowairflow
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