SAIC has an opening for a Big Data Engineer. This is a remote position.
The Big Data Engineer is responsible for designing and developing parallel data-intensive systems using Big Data technologies.
Responsibilities include:
Working with the full open source Hadoop stack and Hadoop-like systems from cluster management, to data repositories, to analytics software, to schedulers.
Working in on-premises or public cloud environments to build scalable systems.
Determining the appropriate database given the data and analytics needs, whether file structures such as HDFS, relational databases including NewSQL, non-relational NoSQL databases including in-memory databases.
Optimizing the distribution of data across nodes and the performance of distributed database, storage and processing systems.
Identifying performance bottlenecks and evaluates scaling benchmarks.
Contributing to the planning, design and implementation of new system implementations and the migration of existing systems to modern and scalable systems.
Qualifications
Typical Education and Experience:
Bachelors and 9+ years of experience; Masters and 7+ years of experience; PhD or JD and 4+ years of experience. Additional experience may be considered in lieu of a degree.
Experience and knowledge of implementation and configuration of distributed systems in the larger Hadoop ecosystem (both open-source and proprietary stacks that leverage these tools).
Knowledge of data modelling and implementing data pipelines and workflows to create scalable and resilient enterprise data solutions.
US Citizenship required.
Target salary range: $100,001 - $125,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.
