Sid Anand
Fellow, Cloud & Data Platform, Global Tech Platform
California, United States
Summary
🤩
Rockstar🎓
Top SchoolSid Anand is a veteran cloud and data platform leader with 11+ years of engineering experience who now serves as a Fellow at Walmart Global Tech, shaping large-scale data systems and platform strategy. He helped bring Apache Airflow into the Apache Foundation and remains a longtime committer, contributing key scheduling, SLA alerting, and encryption features to one of the most widely used workflow engines. A former Chief Data Engineer at PayPal and early cloud data architect at Netflix, Sid has repeatedly built resilient, low-latency streaming and database services at scale and holds multiple patents in stream processing and storage. He also invests in early-stage infrastructure startups as a limited partner and curates technical programs as a QCon co-chair, blending practitioner-driven community building with hands-on architecture. Based in California, he balances part-time hacking with full-time fatherhood, combining deep systems expertise with a track record of operational leadership and open-source impact.
11 years of coding experience
23 years of employment as a software developer
I.B. International Baccalaureate, I.B. International Baccalaureate at American School of ParisM.Eng Computer Science, M.Eng Computer Science at Cornell University
French, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (15)
apache-airflow10
python10
data-pipelines9
data-engineering9
sqlalchemy9
data-pipeline9
workflow-engine9
orchestration9
orchestra9
database-design8
restful-api7
api-design7
api-rest7
rest-api7
gcp6
Programming languages (11)
Github contributions (5)
apache/airflow
Jun 2015 - Jun 2020
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Back-end Developer
Back-end DeveloperContributions:222 PRs, 123 pushes, 17 branches in 5 years
Contributions summary:Sid primarily contributed to the Apache Airflow codebase by implementing and enhancing features related to task management and scheduling, specifically focusing on SLA (Service Level Agreement) miss alerts and callbacks. This involved modifications to core models, jobs, and related migration scripts to add functionality for optional SLA alert callbacks and email notifications. The user also worked on supporting encryption for connection extra fields and variable values, as well as adding the ability to pause DAGs at creation based on a configuration setting.
monitorpythonschedulerapacheprogrammatically
r39132/airflow
Aug 2015 - May 2019
AirFlow is a system to programmatically author, schedule and monitor data pipelines.
Contributions:213 pushes, 56 branches, 1 tag in 3 years 9 months
monitorpythondata-pipelinesprogrammaticallyairflow
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