Senior Data Engineering Specialist

Role Overview

• Provide strategic technical leadership in data engineering, serving as the primary customer-facing expert on DISN network topology data to enable advanced data correlation and enrichment.
• Represent the team in high-level technical discussions and decision-making with internal and external stakeholders, influencing solution design and architecture.
• Architect, design, develop, document, test, and deploy complex software solutions using Python, JavaScript, Java, and SQL, ensuring scalability and maintainability.
• Lead the creation of advanced Kibana visualizations and dashboards, leveraging machine learning capabilities and React to deliver actionable insights.
• Oversee the design and implementation of robust data enrichment pipelines, integrating diverse data sources into Confluent (Kafka) and Elastic platforms.
• Direct the development and management of multi-site Kafka and Elastic clusters, including deployment, configuration, testing, troubleshooting, and maintenance to support mission-critical operations.
• Lead Kafka system integrations between Elasticsearch/Logstash and other enterprise systems.
• Guide Agile collaboration, leading scrum teams, mentoring junior engineers, and fostering a culture of continuous improvement and innovation.
• Communicate and collaborate effectively with geographically distributed teams to ensure alignment and successful completion of project objectives.
• Troubleshoot and resolve complex installation, infrastructure, and system issues; proactively report, monitor, and mitigate technical risks.
• Author, review, and maintain comprehensive technical documentation, including DoD requirements, interface documents, and security compliance artifacts.
• Ensure all solutions adhere to DoD security standards and guidelines, and provide oversight for platform sustainment and reliability, proactively addressing operational challenges.

Requirements

• Bachelor’s degree from an accredited college in a related discipline, or equivalent experience/combined education, with 8-12 years of professional experience; or 6-10 years of professional experience with a related master’s degree.
• 8+ years of experience in software engineering, data engineering, or business/data analysis, with demonstrated leadership in Agile/Scrum teams.
• Extensive hands-on software development experience with Python, Java, SQL, and working knowledge of JavaScript and HTML.
• Advanced experience with distributed version control systems such as Git and Bitbucket.
• Deep expertise in data analytics and visualization tools, including Kibana, Power BI, Tableau, and the ELK stack (Elasticsearch, Logstash, Kibana).
• Proven experience designing, developing, and optimizing ETL processes and complex data pipelines, including integration with event streaming platforms such as Kafka.
• Strong background in data modeling, unification, and analytics to support data-driven projects and advanced enrichment.
• Demonstrated ability to architect and implement application and system integrations, including Kafka and Elastic platform integrations.
• Solid understanding of networking and internet protocols, with experience supporting network-centric and data-driven environments.
• Experience developing and deploying software on UNIX/Linux command line platforms.
• Strong facilitation, stakeholder engagement, and communication skills, with the ability to bridge business and technical perspectives and collaborate with customer representatives, domain experts, systems engineers and architects.
• Experience with Agile project management and collaboration tools such as JIRA and Confluence.
• Demonstrated leadership in mentoring junior team members and fostering a culture of continuous improvement.
• Active Secret DoD Security clearance prior to start date.
• Active Security+ Certification (or other applicable DoD 8570 IAT II certification) prior to start date.

Tech Stack

• ElasticSearch
• ETL
• Java
• JavaScript
• Kafka
• Linux
• Logstash
• Python
• React
• SQL
• Tableau
• Unix

Benefits

• competitive compensation
• Health and Wellness programs
• Income Protection
• Paid Leave
• Retirement