Sid Anand Email & Phone Number

Bentonville, Arkansas, US

Wilmington, Delaware, US

Apache Airflow is an open-source workflow automation and scheduling system that can be used to author and manage data pipelines. As one of its earliest maintainers, I helped bring the Airflow project into Apache and to grow its community, processes, and codebase.

London, GB

• I provide advisory services to startups, conferences, and incubators. These include:
• Celect (acquired by Nike)
• Data Council
• DataZoom
• Etsy
• Niara (acquired by Aruba)

Toronto, Ontario, CA

• QCon is a global family of practitioner-driven conferences with annual events in SF, NYC, London, Munich, Sao Paolo, Beijing, Guangzhou, Shanghai, & AI.
• As a co-chair for QCon, I help curate tracks & talks for the conference, invite speakers & track hosts to participate, and promote programs and practices that spread social change for good in the software industry
• As a track host, I design a track and invite speakers, sometimes speaking myself. I typically host tracks on data engineering, data science, and fault-tolerance.

Encinitas, CA, US

• Datazoom is a Real-time Video Data company. The Datazoom data platform collects and transits video telemetry data with high-fidelity and low-latency to a range of 3rd party data sinks. In my role, I contributed in the.
• Designed the "-ilities" into all of our systems
• Built and managed a fun, healthy, and impactful engineering organization at Datazoom
• Defined and oversaw the implementation of best-practices in all areas of engineering
• Implemented various parts of our software infrastructure

San Jose, CA, US

• As PayPal's first Chief Data Engineer, I led critical, high-value projects, helped grow the technical competence of the organization, and helped to promote PayPal’s external-facing technical brand.
• Managed a team of data scientists developing recommendation algorithms as part of PayPal’s acquisition of Jetlore, a shopping recommender technology company
• Led a team to design & build PayPal’s Streams-as-a-Service (known internally as the Core Data Highway or CDH). CDH offers users a self-service means to launch any data stream on-demand from any source (e.g. RDBMS.
• Led a team to build PayPal’s Database-as-a-Service (DbaaS) platform in GCP. DbaaS offers a self-service portal that allows users to launch and manage DB clusters (e.g. CouchDB, MySQL, Aerospike)
• Helped build a high-quality, high-performance software development practice focused on building software data infrastructure at scale (e.g. streaming systems, data stores, big data processing) in PayPal’s Core Data.
• Helped define a standard engineering hiring process for IC candidates up to Director-level ICs

• Agari tackles the problem of enterprise spear-phish detection and prevention. Agari was acquired by HelpSystems in May 2021. I joined Agari to help design and build nearline fraud prevention systems as a service.
• Designed and built reliable predictive data pipelines in the AWS cloud for bath and near-real time control systems and analytics
• Championed tech branding efforts at Agari (e.g. blogs, podcasts, conference speaking, open-source contributions)

Sunnyvale, CA, US

• I helped develop LinkedIn's novel Search-as-a-Service (Galene) system & search auto-complete (a.k.a. search type-ahead) backend. Typeahead is one of the 3 most visible ways that users interact with LinkedIn. First, a.
• Co-led a 20+-person effort to create LinkedIn's novel Search-as-a-Service (Galene)
• Led a small team to build search type-ahead (a.k.a. auto-complete) on Galene
• Led the search Indexing team, responsible for building offline (Hadoop) and near-real time indexes

Sunnyvale, CA, US

• I joined the Distributed Data Systems (DDS) organization at LinkedIn shortly after LinkedIn's IPO. This organization created and supported online, nearline, and offline data systems at LinkedIn. These included Kafka.
• Led the development of LISTT (LinkedIn Segmentation & Targeting Tool). LISTT is a self-service tool that marketing operations uses to target LinkedIn members for online marketing needs. It does this by leveraging both.
• Presented LISTT at Hadoop Summit 2013

Los Gatos, CA, US

• I was the first engineer at Netflix to work solely on the public cloud as establishing a hybrid data fabric was the first major hurdle to cloud adoption. My goal was to get Netflix's data into the cloud and to keep it.
• Part of a 4-person sub-team that designed and built the world’s first cloud-based video streaming service
• Brought NoSQL to Netflix
• Helped build Netflix’s Cloud-based Data Infrastructure (e.g. Cassandra, SimpleDB, S3, etc...)
• Filed the first 2 patents involving Netflix's new Cloud-based Data Architecture
• Authored a white paper titled “Netflix’s Transition to High-Availability Storage Systems”

Los Gatos, CA, US

• I joined Netflix when there were ~100 people at the company. As a founding member of Netflix's Software Infrastructure team, I helped define, design, and implement core libraries, services, and infrastructure – all.
• Led the identification and resolution of various Denial-of-Service exploits. Evangelized DoS prevention.
• Found and eliminated a critical performance bug in the streaming PC player – this fix reduced DB traffic by 50% to 2 key tables, reducing our need to vertically scale the database
• Increased farm-wide memory headroom by 10% by eliminating the use of a Java Finalizer
• Created Netflix’s Session Manager to deliver consistently fast user response times under high traffic
• Created Netflix’s web request processing framework to improve developer productivity and code robustness

Brooklyn, NY, US

• I started advising the founders of Etsy when they had first started. A year later, Rob Kalin asked me to join Etsy as employee #12 and to run Engineering as Etsy's first VP of Engineering.
• Managed a distributed engineering team
• Doubled Engineering through recruiting / hiring
• Designed and wrote a real-time application logging and analytic application
• Helped design the database data models and layout
• Helped offload database load over to search via Change Data Capture

San Jose, CA, US

• Hot off my successes at the eBay Research Labs, I was invited to join eBay’s Search Engine team to work on a variety of cool search systems
• With help from a co-worker, I built an in-memory database for buyer behavior, central to eBay's new search ranking system (i.e. a second-pass ranker called Best Match).
• Implemented a search service to find (fuzzy) near matches for sellers by user id, first name, last name, or full name

San Jose, CA, US

• After I submitted 7+ innovation ideas to the eBay Research Labs, eBay started an Innovation Rotation program which allowed engineers to rotate into the Research Labs to prototype their ideas. I was given 9 months over.
• Partnered with a colleague to build a WYSIWYG eBay Store builder leveraging the latest browser-side technologies. The goal was to build an engaging eBay Store flow as a responsive single page implementation.
• Designed & implemented a novel P2P version of eBay over Skype. This new version introduced various distributed system state-machine challenges, which I solved with a novel distributed ledger implementation.
• Attempted to build a single-cpu cycle fast filter that could be used for recommenders & search ranking

San Jose, CA, US

• My career at eBay started as a founding member of the Stores & Merchandising team. The dual charter of the team was to build recommender systems and pave the way for eBay Stores (i.e. online seller storefronts hosted.
• Led projects that touched Search, MyEBay, Selling, Buying, Sign-on, API, etc...
• Proposed & led a project to re-architect the eBay subscriptions framework
• Introduced AJAX at eBay! It was a budding new technology at the time.

• Siebel Systems created the CRM market in the late 90s and dominated the market in the early 2000s. Software was sold to customers who were then expected to install it on their servers -- this is well before the advent.
• Ran repeatable & precise scalability benchmarks to quantify scalability degradation
• Executed memory and CPU profiling followed by profile analysis
• Made code changes to regain scalability headroom

M.Eng, Computer Science

B.S, Materials Science & Engineering

I.B., International Baccalaureate