Pranav Bhandari
Software Engineer at Google
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolPranav Bhandari is a software engineer at Google with seven years of experience building backend systems and cloud data pipelines. Comfortable in C++, Java, and Python, he brings a strong foundation in algorithms, OOD, and practical data engineering—evidenced by contributions to Apache Beam and Google Cloud Dataflow templates that improved GCS error handling and added JDBC-to-Pub/Sub/BigQuery integrations. He combines production-grade coding with a focus on reliability and test coverage, having added classloader support and richer error propagation to critical open-source components. A former TA and tutor who boosted student performance through targeted instruction, Pranav pairs technical depth with clear communication across diverse teams. Based in San Francisco and originally from Chennai, he has a track record of turning data integration challenges into robust, maintainable solutions.
7 years of coding experience
Bachelor of Science - BS, Computer Science, Cumulative GPA: 3.8/4.0, Bachelor of Science - BS, Computer Science, Cumulative GPA: 3.8/4.0 at The University of Texas at Arlington
English, Hindi
Stackoverflow
161reputation
3kreached
9answers
0questions
Github Skills (23)
dataflow-programming10
dataflow10
data-engineering10
google-cloud-dataflow10
jdbc10
java10
google-cloud-storage10
gcp10
javas10
error-handling10
apache-beam10
bigquery9
big-data9
pubsub9
streaming8
Programming languages (3)
Github contributions (5)
GoogleCloudPlatform/DataflowTemplates
Nov 2021 - Jan 2023
Cloud Dataflow Google-provided templates for solving in-Cloud data tasks
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:2 releases, 122 reviews, 50 commits in 1 year 2 months
Contributions summary:Pranav primarily contributed to the development of new data pipelines and backend functionality for the Google Cloud Dataflow templates repository. They added new templates, such as the Jdbc to Pubsub and Pubsub to Jdbc templates. They focused on integrating new data sources (JDBC) and sinks (Pub/Sub, Spanner, and BigQuery) into the existing data processing framework, demonstrating expertise in data integration and cloud technologies. The commits also included adding new parameters to template options and increasing the coverage in testing to ensure code quality.
gcpgoogle-cloud-platformgoogle-cloudgoogle-cloud-storagedataflow
apache/beam
Jul 2022 - Oct 2022
Apache Beam is a unified programming model for Batch and Streaming data processing.
Role in this project:Back-end Developer
Back-end DeveloperContributions:39 reviews, 4 commits, 28 PRs in 3 months
Contributions summary:Pranav primarily focused on improving the Google Cloud Storage (GCS) interaction logic within the Apache Beam Java SDK. Their commits addressed error propagation from GcsUtil, improving the handling of exceptions related to bucket accessibility, and enhancing error messages. The contributions also involved adding classloader support to the JDBC integration and implementing a new parameter for driver jars to improve the functionality of JDBC. These changes directly relate to improving the reliability and functionality of data processing within the Beam ecosystem.
golangpythonstreaming-databeambatch
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