Lead Platform Engineer - Java Spring

Los Angeles, CA, United States • $150k - $180k


Role Location

  • Los Angeles, CA, United States


$150k - $180k


101 - 250 people


6420 Wilshire Blvd Ste 880
Los Angeles, CA, 90048, US

Tech Stack

  • Java
  • PHP
  • Spring MVC
  • Tomc
  • Laravel
  • Vue.js
  • JavaScript
  • CSS
  • HTML
  • Webpack
  • Redis
  • Elastic Search
  • MongoDB
  • M

Role Description

You will be designing and implementing web-based Java Spring Applications that power our site. The Ranker technology stack consists of custom CMS framework built on Spring MVC running inside Tomcat.

Leveraging data sets of millions of entities, we aggregate linked data graphs into Ranker to expose them to our user base for our list building platform. Large scale data processing and Ranker go hand-in-hand as we continue to target structured data sets of value to augment our existing knowledge base.

The Ranker Back End Engineering team is responsible for building and maintaining the high trafficked site, a distributed app and most importantly large scale data aggregation.

About Ranker

Ranker is a crowdsourced platform that attracts more than 30 million consumers visit a month to view, rank, and vote on broad opinion-based questions ranging from the Best Board Games to Hottest Celebrities to Best Inexpensive Cars, Ranker is the “Yelp for everything else” to consumers. Outside of a few verticals such as travel and restaurants, crowdsourced rankings are hard to find, even as consumer demand for opinion-based answers is far outpacing other queries.

A Quantcast Top 50 site, Ranker has built a solid, rapidly growing advertising and affilate ecommerce business as a publisher where consumers find highly credible, crowdsourced answers. Equally importantly, Ranker is a fully datacentric company - the enterprise value of our proprietary data may dwarf the consumer business. Our uniquely engaging interface (10% of visitors to votable rankings vote, on 21 items per visit) is the hook for a fully-semantic consumer data collection machine. This data produces continually updated rankings with intrinsic value far beyond regular pageviews and has in parallell built an “opinion graph” (people who like X also like Y, and think Z is expensive) with 6 million “edges”. Due to the datacentric way Ranker was architected, our graph is fully “clean” data, requiring no messy postprocessing or natural-language-processing. This data has immense value to market researchers, ad agencies, ad targeters, and other enterprise customers who derive value from consumer psychographics.

Company Culture

Though have been around for a while we still operate like a startup . Employees that like to wear many hats and be creative and forward thinking about solving problems are our ideal candidates. Our dev team is close nit (dev / product / qa) and we value not only technical skills but social skills as well!

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