Huawei is hiring a Bigdata Chief ARchitect

Chief Architect, Big Data Bangalore, India About the position Huawei has become an industry leader in fixed and mobile networks. The future of networking is moving strongly towards a converged model for CT & IT technologies. In response to a growing demand from our customers, Huawei has started a R&D effort focus on providing a scalable, multi-tenant computing and communication infrastructure platform capable of serving the needs of CT & IT customers. Big Data team at Huawei India R&D center is looking for distinguished architects to drive innovation in our big data platform offerings. If you are passionate about big data storage technologies, including distributed file systems, noSQL data stores, and related open source projects such as HDFS and HBase, desire to optimize big data engine components to solve customer use cases, lead architecture design, and resolve challenging technical problems, Huawei is a place you should consider for your next career move. Responsibilities: This position will working closely with members at Huawei's Product/Platform team in China, and Big Data R&D in USA, he will be responsible for: · Define short term and long team Business roadmap for BigData business that can address customer pain points and help deliver competitive products (on top of our platform offering) · Architect and design our next generation storage engine and ecosystem that are secure and reliable at large scale. · Understand the challenges of storage engine in big data area. Design and innovate technologies or solutions for distributed storage engine and through POC and collaboration with internal and external partners. · Deliver rapidly iterative new design and/or new technology POC as well as releases. Desirable · Experience with large-scale, distributed systems design and development · Hands on engine experience in one or more column/row storage database system (Sybase IQ, InfiniDB, MonetDB, Infobright, GreenPlum, Postgres etc), or distributed file systems (HDFS etc). · Experience in Hadoop eco-system is a plus (YARN, Spark, MR, HDFS, HBase, Hive, etc.) · Excellent written and verbal communication skills. · Experience in working in a distributed team environment is a plus.