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Posted: Saturday, March 11, 2017 12:22 AM

About Uber Uber is a technology company that is changing the way the world thinks about transportation. We are building technology people use everyday. Whether its heading home from work, getting a meal delivered from a favorite restaurant, or a way to earn extra income, Uber is becoming part of the fabric of daily life. Were making cities safer, smarter, and more connected. And were doing it at a global scale:energizing local economies and bringing opportunity to millions of people around the world. Ubers positive impact is tangible in the communities we operate in, and that drives us to keep moving forward.We are looking for skilled and motivated engineers to help create the data platform that will enable Uber, as we move real people and things, in the 300+ cities across the world. You will expand on a solid data infrastructure, that collects, stores and serves petabytes of information, services and frameworks that makes data more accessible to Ubers developers, services and teams. For example, you will be building out a machine learning pipeline, that extracts standard sets of features out of our most important datasets, and exposes them as Spark RDDs. You will be tasked with implementing SDKs for accessing the vast datasets we house and managing periodic computations, to keep our products and services up to date. You will be creating several gateway services, that offer low latency access to information in our Hadoop data lake. You will be working on creating sophisticated geospatial libraries, that can help our developers quickly build value on top of our troves of geo data. You will utilize the latest breakthroughs in data processing technologies, to extract enormous value out of Ubers data. Fundamentally, you will be working with a team of stellar colleagues, and contribute to the next generation of intelligent data services that will have a profound impact on how we march towards the vision of of Ubers data driven, real:time marketplace. Working on data at Uber now, is an exciting opportunity as we need to balance the companys needs to move fast today while continuing to create platforms that will be leveraged for the products of tomorrow. Does this sound rewarding to you? Are you a demonstrated team player, smart at execution and love data? We want to hear from you. What youll needDeep engineering background, ideally experienced with large scale data/distributed systems, housing several TBs of dataDedication to moving fast in the short:term, while simultaneously building for long termDeep and Hands on experience building MapReduce/Spark or similar such big data pipelines/frameworks/servicesPrior experience developing foundational services at scale (eg: ML Pipelines, Relevance systems, Search services)Can quickly learn and be productive at new data technologiesCan produce quality code fast, preferably Java/Scala on *nixExcellent foundation in distributed systems concepts Were bringing Uber to every major city in the world. We need your skills and passion to help make it happen Be sure to check out the Uber Engineering Blog to learn more about the team.PerksEmployees are given Uber credits every month.The rare opportunity to change the way the world moves. Were not just another social web app, were moving real people and assets and reinventing transportation and logistics globally.Smart, engaged co:workers. Benefits401(k) plan, gym reimbursement, nine paid company holidays.Full medical/dental/vision package to fit your needs.Unlimited vacation policy; take time when you need it. Uber is an equal opportunity employer and enthusiastically encourages people from a wide variety of backgrounds and experiences . Uber does not discriminate on the basis of race, color, religion, sex (including pregnancy), gender, national origin, citizenship, age, mental or physical disability, veteran status, marital status, sexual orientation or any other basis prohibited by law.


• Location: San Francisco

• Post ID: 57158118 sf is an interactive computer service that enables access by multiple users and should not be treated as the publisher or speaker of any information provided by another information content provider. © 2017