5-7 years of experience in software engineering with a focus on big data technologies.
Proficient in Hadoop ecosystem components including MapReduce, Accumulo, and Zookeeper.
Strong troubleshooting skills for HDFS and Accumulo environments.
Experience with Kubernetes for deployment and management of applications.
Ability to develop and execute Ansible playbooks for automation tasks.
Primary programming language expertise in Java.
Familiarity with data warehousing concepts and processing pipelines.
Responsibilities
Set up, deploy, and maintain Hadoop, MapReduce, Accumulo, and Zookeeper environments.
Troubleshoot and resolve issues related to HDFS nodes and Accumulo processes.
Develop and run Ansible playbooks for system automation.
Write and optimize MapReduce applications for data processing.
Create and manage Accumulo iterators and handle data ingestion processes.
Collaborate with team members to enhance data processing pipelines.
Ensure system reliability and performance through proactive monitoring.
Benefits
Opportunity to work with cutting-edge big data technologies.
Collaborative team environment focused on innovation.
Professional development opportunities in advanced data engineering.
Flexible work arrangements to support work-life balance.
Full Job Description
The Common Services team is sourcing for a SWE2 candidate with experience in the below: - Experience setting up, deploying, and troubleshooting Hadoop, Map / Reduce, Accumulo and Zookeeper - this also extends to current sustainment tasking. - Tasking would also include troubleshooting and fixing issues - for example off lining an HDFS node because of a bad disk. Off lining an Accumulo tserver processes because of bad memory... - Familiar with Kubernetes deployment and troubleshooting. - Familiar with and able to develop and run ansible playbooks. - Primary development language would be Java. - Experience writing Map / Reduce applications. - Experience writing Accumulo iterators and using scanners and Accumulo ingest (streaming and bulk imports) - Familiarity with the Data Warehouse and their processing pipelines.
