Software Developer Integration Engineer

Experience Requirements:
B.S. in Computer Science Mathematics Physics Electrical Engineering or Computer Engineering and 5 years of combined experience in Kafka Java RESTful services AWS and full stack development. Must hold an active Interim Secret DoD Security clearance. Ability to obtain Security certification or equivalent DoD 8570 IAT II certification within 14 days of the start date. Software development experience with Python Java and SQL. Working knowledge of HTML and JavaScript. Advanced understanding of event streaming and Kafka integration. Experience in application integration design and strong communication skills for collaboration with virtual teams. Experience in developing detailed software designs particularly in ksql or kstreams. Proficiency in following a software development lifecycle and maintaining productionquality code. Experience with distributed version control software such as Git and Bitbucket. Knowledge of and ability to apply principles theories and concepts of Software Engineering. Experience developing software on a UNIX command line platform. Develop DoD requirements traceability and detailed plans/schedules. Write software systems engineering documents and interface documents (IDDs/ICDs). Preferred Qualifications: Text Mining & ELK Stack: Experience with text mining tools and techniques including ELK Stack for summarization search and entity extraction. CI/CD & DevOps: Familiarity with CI/CD techniques containerized pipelines and DevOps practices. Search & Analytics Applications: Experience with BI tools like Kibana and Splunk and technologies like Elasticsearch Logstash Kafka and NiFi. Kubernetes & Agile: Familiarity with Kubernetes deployment Agile methodologies and tools. Cloud Expertise: Familiarity with AWS GovCloud and cloud infrastructure including networking and security policies. Cloud Platform Expertise: Utilize expert knowledge of cloudintegrated platforms for integration and deployment tasks. CrossTeam Collaboration: Work within a matrixed organization collaborating with project leadership and core GMS teams to combine software and integration practices with data engineering. System Architecture & Operational Stability: Apply knowledge of system architecture networks and Centralized Logging (ELK) to support data transformation initiatives. Cloud & DoD Environments: Experience developing and deploying software in a DoD environment (DISA experience is a plus) including experience building and deploying software applications that meet DoD security standards including updating applications and code to meet security scans and meeting security implementation guidelines (e.g. STIGs). Agile Processes: Experience with Agile methodologies and related tools. Experience with Atlassian tools including JIRA and Confluence. Certifications: Certified Confluent Developer and Certified Elastic Engineer. Remote Teamwork: Experience working remotely with a geographically dispersed team. This role offers the opportunity to work on advanced integration projects combining software engineering with data integration in a dynamic environment. If you meet the qualifications and are passionate about integration engineering we encourage you to apply.

Essential Requirements: US Citizenship is required. Active Secret

Job Duties:
Integration Solutions: Develop and implement integration solutions for the JMT project using Kafka and Elastic as the primary data architecture platforms. Data Integration: Integrate data sources (ServiceNow Terminal Cert DB Modem Cert DB Baseband Mission Workup TRS MRS UDL) into Confluent (Kafka) and Elastic platforms. Develop Kafka system integrations between Elasticsearch/Logstash and other systems. Kafka Integration & Development: Develop Kafka system integrations custom connectors and work with ksqlDB and Kafka Streams for data processing based on the design solution. Kafka Cluster Management: Deploy and manage Kafka clusters on Kubernetes in multisite environments (both onpremise and cloud). Software Lifecycle Automation: Automate the full software lifecycle from design and development to testing and deployment including production environments. DevOps Pipelines: Design and build application deployment pipelines including containerized environments using Kubernetes and Docker and automated testing pipelines.