Track Host: Sid Anand

He / him / his

Fellow, Cloud & Data Platform @Walmart, Apache Airflow Committer/PMC, Ex-Netflix, LinkedIn, eBay, Etsy, & PayPal

Sid recently joined Walmart (i.e. Walmart Global Tech) as a fellow to work on all things data. Prior to joining Walmart Global Tech, Sid served as the Chief Architect and Head of Engineering for Datazoom, where he and his team built high-fidelity, low-latency data streaming systems. Prior to joining Datazoom, Sid served as PayPal's Chief Data Engineer, where he helped build systems, platforms, teams, and processes, all with the aim of building access to the hundreds of petabytes of data under PayPal's management. Prior to joining PayPal, Sid held senior technical positions at Netflix, LinkedIn, eBay, & Etsy to name a few. He earned my BS and MS degrees in CS from Cornell University, focusing on Distributed Systems.

Outside of work, Sid advises early-stage companies and several conferences. Once an active committer on Apache Airflow, he is now mostly a fan.

Sid's body of work includes but is not limited to :

  • The world's first cloud-based streaming video service -- I was the first engineer to work on the cloud at Netflix
  • LinkedIn's Federated Search Typeahead (a.k.a. auto-complete)
  • LinkedIn's (Big Data) Self-service Marketing Analytics tool
  • PayPal's DBaaS - an internal self-service system to provision & manage heterogenous databases
  • PayPal's CDC - an internal self-service CDC system to stream DB updates to nearline applications
  • eBay-over-Skype : Following the Skype-acquisition, I built a P2P version of eBay offers
  • eBay's Best Match Search Ranking Engine powered by an In-Memory Database
  • eBay's Fuzzy-match name/email Search
  • Agari's Data Platform : Batch & Streaming Predictive Data Platform as a Service
  • Datazoom's Platform : High-fidelity, Low-latency Streaming Data Platform as a Service

Find Sid Anand at:

Track

Innovations in Data Engineering

Which technologies and practices live up to their promises? What patterns and technologies have stood the test of time? What are some pitfalls that you need to be aware of? Come to this track to learn from data engineers facing & solving these problems today.

Date

Tuesday Apr 9 / 10:35AM BST

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