Peixian Wang, Developer in New York, NY, United States
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Peixian Wang

Verified Expert  in Engineering

Back-end Developer

Location
New York, NY, United States
Toptal Member Since
September 22, 2022

Peixian is an experienced back-end engineer working with high-performance C++, Python, and Elixir. He also has deep experience in Kubernetes native applications and a bachelor's degree in computational astronomy. He has worked on highly scalable systems, including video delivery at Vimeo, cloud metrics at Datadog, and complex financial pricing systems at Bloomberg. Peixian's most recent experience is as a senior Elixir developer for Sleeper, a fantasy sports iOS and Android gaming app.

Portfolio

Sleeper
Elixir, Kubernetes, Google Cloud, Amazon Web Services (AWS), ScyllaDB, Helm...
Bloomberg
C++, Natural Language Processing (NLP)...
Datadog
Go, Google Cloud, Alibaba Cloud, Amazon Web Services (AWS), Azure, Amazon EC2...

Experience

Availability

Part-time

Preferred Environment

Linux, Python, Elixir, C++, Go, Kubernetes, Amazon Web Services (AWS), Google Cloud Platform (GCP)

The most amazing...

...project I've worked on involved carefully tuning Cassandra and the data networking layer to optimize for the lowest possible latency.

Work Experience

Senior Elixir Developer

2022 - PRESENT
Sleeper
  • Developed and migrated Elixir remote procedure call (RPC) systems to Kubernetes, with shared virtual private cloud to Scylla Cloud.
  • Performed Helm migration, monitoring, and tracing for the entire back-end stack.
  • Rolled out compliance changes for daily fantasy sports gaming across 25 states.
Technologies: Elixir, Kubernetes, Google Cloud, Amazon Web Services (AWS), ScyllaDB, Helm, GraphQL, APIs, Retool, Google Cloud Platform (GCP), Algorithms, Data Scraping, Web Development, Web Scraping

Senior Software Engineer

2018 - 2022
Bloomberg
  • Developed and worked on multi-asset risk systems, deploying and refining Cassandra calls to be sub-50 milliseconds.
  • Built out the entire Kubernetes and Docker management system to deploy a custom NLP pipeline, including automatically training against new datasets and blue-green deployments for production.
  • Contributed to building a Lex/Yacc-based parser to traverse and perform named entity recognition and disambiguation.
Technologies: C++, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Low-latency Software, Finance, Private Clouds, Python, Cassandra, Kubernetes, Programming Languages, Django, JavaScript, APIs, Algorithms, Data Scraping, Web Development, Web Scraping

Go Developer

2018 - 2018
Datadog
  • Developed a gevent-based Python application to track all cloud metrics from Azure, deploying it across all Azure products.
  • Built and deployed a Go gRPC-based application that integrated with Stackdriver to track all cloud metrics from the Google Cloud Platform.
  • Managed AWS metrics and monitored systems, allowing customers to see their AWS events within Datadog.
Technologies: Go, Google Cloud, Alibaba Cloud, Amazon Web Services (AWS), Azure, Amazon EC2, Django, Amazon DynamoDB, Amazon RDS, JavaScript, APIs, Google Cloud Platform (GCP), Algorithms, Web Development, Web Scraping

Back-end Developer – Upload

2016 - 2018
Vimeo
  • Led the Kubernetes migration from on-prem services into Google Cloud Platform for the back end of Vimeo.
  • Built resumable uploads within Vimeo while contributing to the Tus resumable upload protocol standard.
  • Managed and worked on systems for video delivery across points of presence (POPs) with Fastly using Varnish.
Technologies: Go, Python, Fastly, Varnish, Google Cloud, Amazon EC2, Django, Amazon DynamoDB, Amazon RDS, Video Compression, JavaScript, APIs, Google Cloud Platform (GCP), Algorithms, Web Development, Web Scraping

Technical Architecture of a Distributed Tracing Mechanism

At Bloomberg, we ran a monolithic service that called out to over 30 other services. Each downstream service was responsible for a single asset type, such as commodities, mortgages, and corporate bonds.

With so many requests and services in flight, we would run into pricing instability errors; the numbers returned from a downstream service were not deterministic, where the same request would yield different results. This presented a problem for us since our service had to call out to multiple asset types, then compute a price based on the prices of the underlying assets; for example, pricing a corn future requires a call to the downstream commodities prices service.

We opted for a full request-tracing mechanism to track down and debug non-deterministic requests. I handled the technical architecture and the first implementation of tracking all messages.

Development of a Kubernetes Acceptance Testing System

We had a team that had just experienced attrition from six to two people within a month and had a new team lead as part of that process. The team needed to quickly rebuild and scale up, as they maintained services that parsed information from real-time news feeds. However, the services were legacy and were built upon a combination of parser-based logic and machine learning information extraction tools. Most of the maintenance information had also been left with the former team members. I was brought in to help reduce tech debt, document all information, refactor as necessary, and help out any way I could.

Given that I didn't know the code, I decided it might be best to treat it as a black box. Since all the services were self-contained binaries with some configuration INIs, I sketched out a rough design of how each service interacted with another and which datastores were called by each service. I compiled this information into a variety of Helm deployment charts. I then set up a system to sample a portion of each day's incoming requests and responses, for each service, into a log that could be replayed.
2012 - 2016

Bachelor's Degree in Computational Astronomy

University of Illinois, Urbana–Champaign - Urbana–Champaign, Illinois, United States

Tools

Retool, Helm, Fastly, Varnish

Platforms

Kubernetes, Linux, Google Cloud Platform (GCP), Amazon Web Services (AWS), Amazon EC2, Azure

Languages

C++, Python, Go, Elixir, GraphQL, JavaScript

Frameworks

Django

Storage

Google Cloud, Cassandra, Amazon DynamoDB, ScyllaDB, Alibaba Cloud

Paradigms

High-performance Computing (HPC)

Other

Apache Cassandra, APIs, Algorithms, Web Development, Finance, Video Compression, Data Scraping, Web Scraping, Natural Language Processing (NLP), Low-latency Software, Private Clouds, Programming Languages, Amazon RDS, Generative Pre-trained Transformers (GPT)

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