MPP Database Engineer
We’re building a new type of distributed analytical query and execution layer that combines traditional SQL concepts with newer technologies like JSON, MongoDB and Hadoop. We’re looking for strong engineers to work within a dedicated team and an awesome community to build a groundbreaking open source product. You’ll innovate on topics including high performance query optimization, querying nested schemaless data, distributed scheduling and latency/laggard management, memory allocation planning and field-striped storage techniques—all sponsored by MapR Technologies, a leading provider of Hadoop.
The cool stuff you get to do :
Interesting deep-dive technical challenges
Mentally engaging, invested coworkers
Build or hone skills working with leading big data technologies like Cassandra, Riak, Hadoop, HDFS, AVRO, MongoDB, Zookeeper.
Become a major contributor and potential committer of an important open source Apache project
Open source job protection and security
Quiet time for technical research
Ability to talk to and show anybody what you’re working on (including going to and presenting at many technical conferences--as you desire)
Upside and flexibility of a startup with stability of a mid-stage company
What you need to have to succeed:
Strong programming experience with a desire to be hands-on
5,000+ hours of experience programming complex systems in Java or C++
Experience building distributed systems, query processing, database internals or analytic systems
The stuff that would be nice to have:
Strong understanding of SQL
Past architecture experience with Hive, Hadoop, NoSQL tools such as HBase, Cassandra or MongoDB, Postgris
About Apache Drill:
Apache Drill is a new Apache incubator project sponsored by multiple leading big data companies. It's goal is to provide a distributed system for SQL based interactive analysis of large-scale datasets. Inspired by Google's Dremel technology, it aims to process trillions of records in seconds.
About MapR Technologies:
MapR Technologies provides the leading distribution for Hadoop. MapR’s Hadoop stack combines optimized versions of open source technologies including Apache HBase, Hive, Pig, and MapReduce, an enterprise-grade NoSQL solution in M7, a powerful data management layer and enterprise reliability features to power companies’ Big Data analytical needs. Founded in 2009, MapR is well funded by leading VCs, already has substantial revenue and carries an enviable customer base that includes leading Fortune 100 companies as well as top technology companies.
MapR Technologies, Inc. is an equal opportunity employer.