Principal Software Engineer

San Francisco, CA, United States

Azure Big data teams present interesting challenges in technologies such as big-data, cloud, storage and open-source. We build reliable, highly scalable and highly performing distributed systems for data analytics on Azure. We work with various open-source technologies like Hadoop, Yarn, etc., and make contributions to these technologies. We are creating a planetary scale storage system, which can scale to Exabyte of data (yes, that’s 18+ digits!). Azure services is building next generation globally distributed, elastic scale, multi-model cloud database services. It is designed to enable developers to build planet-scale applications. This is a once in a lifetime opportunity to be part of a very agile team, take on hard distributed system problems and ship high impact features at a rapid pace. 




Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.


Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.


As an engineer, you have an opportunity to work on the latest technology in compute and container hosting to build a massively scalable unified cloud service framework, get to work on heterogeneous transport protocols, apply innovative algorithms for solving placement and load balancing problems at scale. We need collaborative developers who can think big, deliver on those big challenges, and along the way, change the world. We're looking for engineers to build them from the ground up. Want to change the world with data and large-scale distributed systems? Do you want to solve challenges that you didn’t even know existed until you get to a large size? Come join us on the Azure Big data team!


Basic Qualifications: • 3+ years of programming experience in Java OR C++ OR C# OR C OR object-oriented programming


Preferred Qualifications: • Bachelors degree in Computer Science or Engineering or Mathematics or Physics or IT related technical discipline • Great curiosity and willingness to question • High enthusiasm, integrity, ingenuity, results-orientation, self-motivation, and resourcefulness in a fast-paced competitive environment. • Love the next problem, the next experiment, the next partner • Have a deep desire to work collaboratively, solve problems with groups, find win/win solutions and celebrate successes • Get excited by the challenge of hard technical problems • Solve problems by always leading with deep passion and empathy for customers • Knowledge of Apache Hadoop, Apache Spark, Apache Hive or other big data tools • Knowledge of distributed systems. The REEF.Net team is a core systems infrastructure team tasked with supporting primarily machine learning workloads and other YARN workloads on very large data sets. You’ll be joining a team focusing on supporting machine learning and other applications on distributed infrastructure. We build a framework that enables developers to author extensions to the distributed processing model available in Azure Data Lake and Cosmos. We are grounding this experience first using Machine Learning as an application and abstract out the learnings to build a more generic experience. This position offers an exciting opportunity to practice the field of distributed systems and gain experience in building core backend infrastructure.


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