Spark Developers

Splice Machine’s predictive platform solution helps companies turn their Big Data into actionable business decisions. Our predictive platform eliminates the complexity of integrating multiple compute engines and databases necessary to power next-generation enterprise predictive AI and Machine Learning applications.

As a Distributed Systems Engineer on the Product Development team you will build out Splice Machine’s Hadoop and Spark compute engines while leveraging Splice Machine’s RDBMS ACID-compliant, analytical, transactional, and mixed workloads. This team frequently works on different layers of the Splice Machine stack building fundamental infrastructure components and capabilities that everything else relies on. You will have the unique opportunity to work on a variety of open source and proprietary technologies that will significantly impact our product and business.

About you
You have expert knowledge of distributed computing, parallel programming, concurrency control, transaction processing, and databases. You optimize and refactor other people”s code as well as your own using a variety of programming language, preferably Java.
You make pragmatic engineering decisions in a short amount of time while ensuring your work promotes product stability, reliability, and maintainability.
You build systems to manage and process large data sets distributed on multi-server, cloud-based systems from inception to execution.
You use or are at least familiar with open source technologies that solve big data problems like Apache HBase, Apache Spark, Apache Calcite, Apache Orca, Apache Arrow, Apache Presto, Apache Parquet, Apache Vertica or Apache.

About What You’ll Work On
Building systems that manage and process large data sets and develop components/subsystems of a multi-server cloud-based system.
Design and build a disaster recovery architecture for zero data loss with transactional integrity.
Lead our query optimization team using state of the art sketching algorithms to achieve most efficient queries.
Contribute to our Open-Source database and related Apache projects.
The opportunity to go outside your normal duties and work on our blog, attend hackathons and conferences, speak at events, and anything else you’re interested in that can add to our community.