Tao Feng
Software Engineer at databricks amundsen-io apache
San Francisco, California, United States
Summary
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RockstarTao Feng is a software engineer with 11 years of experience focused on data infrastructure, cataloging, and workflow orchestration, currently working on engineering leadership at Databricks for Data Catalog and Data Lineage. He is a proven open-source maintainer—an Apache Airflow PMC committer and co-creator of Amundsen—who contributes across backend, frontend, and ingestion pipelines to improve discoverability and reliability of data platforms. His work spans optimizing DAG loading and metrics in Airflow to building robust Kafka- and Elasticsearch-backed ingestion for Amundsen, demonstrating comfort with both systems and developer UX. Based in San Francisco, he blends hands-on coding with cross-team coordination to deliver scalable metadata solutions. Less obvious: he moves fluidly between changing UI affordances and deep backend instrumentation, so he can both improve developer-facing tools and tune production performance.
11 years of coding experience
Github Skills (42)
apache-airflow10
python10
back-end-development10
data-engineering10
amazon-elasticsearch10
data-modeling10
discovery-service10
kafka10
workflow-engine10
metadata10
elasticsearchquery10
discovery10
front-end-development10
aws-elasticsearch10
airflow10
Programming languages (12)
Github contributions (5)
amundsen-io/amundsendatabuilder
May 2019 - Apr 2021
Data ingestion library for Amundsen to build graph and search index
Role in this project:
Back-end Developer
Back-end DeveloperContributions:64 releases, 131 reviews, 106 commits in 1 year 11 months
Contributions summary:Tao primarily worked on improving the data ingestion pipeline for the Amundsen data catalog. Their contributions included fixing exceptions, altering the Elasticsearch address, and adding a Kafka source extractor. They made changes to the `elasticsearch_publisher.py` and added functionality to handle the Kafka messages using transformers, adding support for different table and column tags. These changes helped enhance the functionality and robustness of the data ingestion process.
operationdatawarehouseindexdata-ingestionetl-framework
amundsen-io/amundsen
Feb 2019 - Jan 2023
Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.
Role in this project:Back-end Developer
Back-end DeveloperContributions:9 releases, 340 reviews, 437 commits in 3 years 11 months
Contributions summary:Tao primarily contributed to the development of the `amundsen` project, focusing on core features related to data discovery. Their work involved modifying the `sample_data_loader.py` script to improve the loading of sample data. Furthermore, the user added a `User` node with different attributes, demonstrating their involvement in expanding the data model for user-related functionality. Finally, their commits included changes to enhance the project's architecture and data flow.
scientistspythondatadata-scienceanalysts
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