Big Data Engineer
BitTorrent is the world’s largest peer-based technology company. We’ve created a globally recognized ecosystem of technology protocols, consumer software, and electronics devices that help people find, share and move digital media. Our technologies are used by hundreds of millions of people around the world and drive between 20% and 40% of global Internet traffic.
We are a profitable, multi-national company that is backed by some of the world's leading investors, including Accel Partners (Facebook, Groupon, Dropbox, AdMob, etc.) and DCM (About.com, Foundry Networks, Sling Media, Clearwire, etc). Our company is led by a team of proven entrepreneurs that have generated billions of dollars in shareholder returns. We're looking for talented and motivated people to join our rapidly growing team.
BitTorrent offers a unique and compelling work environment. We are proponents of the open Internet and we serve one of the largest user demographics in history. We take these responsibilities seriously and hire accordingly. We work with only the brightest engineers and the most talented business people we can find. Everyone on our team is here to do meaningful work with broad reaching impact. We have a fun yet challenging work environment that fosters diversity, creativity and teamwork. Our team members receive industry leading salaries, stock options, premium benefits, and state-of-the-art offices in San Francisco’s SOMA district.
As a Big Data Engineer on our Data Science team, you will design, develop and deploy data-driven software to solve business problems using the most appropriate techniques in “Big Data” (our data is actually big). You will support experiments and testing on a software platform with 40MM+ daily active user; Build cutting-edge data processing pipelines that deliver answers that drive the present and future of internet and design/specify the data required for analysis, both today and in the future (i.e.: the types of data, granularity of collection, and how much history to retain)
Ideal candidates will posses a strong combination of the following experience:
- Demonstrated “scrappiness” and follow-through in solving problems
- BS or MS degree in Mathematics, Computer Science, Statistics, Operations Research, or other quantitative field
- Experience with failure-tolerant or otherwise highly-available (HA) systems
- Experience with operational maintenance of multi-node/distributed systems (“devops”)
- Comfort with the art and science of extracting insight from massive, unstructured data sets
- Strong grasp of database structure, design, query languages (e.g. SQL), fundamentals of mathematics, large data sets, distributed systems, and statistical concepts
- Deep knowledge of analytic methodologies from domains such as signal processing, optimization, statistical mechanics, econometrics, etc.
- Experience with analytical tools, both “big” data and “small” (e.g., Hadoop, Apache Spark, numpy, Hive, Excel, R, Weka, etc)
- Creativity and curiosity to go beyond current tools to deliver best solution to the problem
- Solid understanding of data flow patterns and architectures
- Experience sharing insights and recommendations to audiences with varying levels of analytic understanding
- Ability to communicate complex concepts in easy-to-understand terminology
- Ability to work effectively across functions, disciplines, and levels
- Interest in working with teammates to explore the question “What else can our data tell us?”