Data Engineer

Join Leidos' Digital Sector as we stand up a brand-new Agile development team at the forefront of federal IT modernization, delivering real digital transformation where it matters most. This is a rare ground-floor opportunity to architect, build, and integrate cutting-edge infrastructure solutions in support of some of our nation's most sensitive and critical missions.

What to expect:

• Early-stage flexibility with partial telework during initial development phases
• Full-time on-site presence at secure facility in Washington, DC will be required as the program matures
• A collaborative, Agile environment where your input shapes the architecture from day one
• Dev platform based on ServiceNow, Elastic, Kafka, AWS and RedHat

What you'll need:

• An active TS/SCI clearance (required for consideration)
• Willingness to complete and maintain additional customer suitability screenings throughout employment
• Current Security+ certification or higher/equivalent

Primary Responsibilities:

• Gather, clean, and validate data from multiple sources to ensure accuracy, consistency, and usability.
• Analyze complex datasets to identify trends, patterns, and insights that answer operational and business questions.
• Design and develop interactive dashboards, reports, and visualizations using Kibana as the primary tool, ensuring findings are communicated clearly and effectively to stakeholders.
• Applying the basics of visual design (i.e. UI) principles in their design work such as visual hierarchy, proximity, similarity, font selection and color theory and demonstrate an understanding of visual, layout, content organization, and accessibility guidelines.
• Translate analytical results into actionable recommendations and present findings to technical and non-technical audiences.
• Engage with stakeholders to understand business needs, operational challenges, and data requirements.
• Refine and maintain data transformation pipelines, ensuring data quality, reliability, and alignment with business logic.
• Develop and maintain self-service analytics tools and reusable data assets to empower end users.
• Document data models, business logic, transformation processes, and analytics workflows for transparency and knowledge sharing.
• Work closely with data engineers, business analysts, and other stakeholders to deliver integrated data solutions.

Basic Qualifications:

• Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related technical discipline and 8+ years of relevant experience. Add'l experience may be considered in lieu of degree.
• An active TS/SCI clearance
• Willingness to complete and maintain additional customer suitability screenings throughout employment
• Current Security+ certification or higher/equivalent
• Demonstrable experience designing and building data visualizations and dashboards using Kibana.
• Hands-on experience with data cleaning, transformation, and analysis using tools such as Python (pandas, numpy), SQL, or R.
• Strong understanding of data modeling, ETL processes, and data pipeline development.
• Ability to translate business requirements into technical solutions and actionable insights.
• Excellent communication skills, with the ability to present complex data findings to diverse audiences.
• Experience with version control systems (e.g., Git) and collaborative development environments.
• Strong attention to detail and commitment to data quality and reliability.
• Strong communication and documentation skills for collaboration and knowledge sharing.
• Experience in application integration design and strong communication skills for collaboration with virtual teams.

Preferred Qualifications:

• Experience with Elastic Stack (Elasticsearch, Logstash, Kibana) for data analysis and visualization.
• Experience with other data visualization tools such as Tableau, Power BI, Grafana, or similar.
• Experience developing self-service analytics solutions and reusable data assets.
• Familiarity with Agile methodologies and project management tools (e.g., JIRA, Confluence).
• Experience with cloud-based data platforms (AWS, Azure, GCP) and big data technologies.
• Knowledge of data governance, security, and compliance best practices.
• Experience documenting data models, business logic, and transformation processes.
• Experience working in mission-driven or operational environments.
• Experience developing and deploying software in a DoD environment (DISA experience is a plus).
• Experience with DISA and DoD Networks.
• Understanding of network routing devices and network device configurations
• Experience with text mining tools and techniques, including ELK Stack for summarization, search, and entity extraction.
• Familiarity with CI/CD techniques, containerized pipelines, and DevOps practices.
• Familiarity with Kubernetes deployment, Agile methodologies, and tools.
• Familiarity with AWS GovCloud and cloud infrastructure, including networking and security policies.
• Experience with Agile methodologies and related tools. Experience with Atlassian tools, including JIRA and Confluence.
• Strong understanding of Agile methodologies, including Scrum and SAFe.
• Experience working remotely with a geographically dispersed team.
• Excellent communication and collaboration skills, with the ability to engage with customers, stakeholders, team members.

#cmpss

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.

Original Posting:

September 23, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $92,300.00 - $166,850.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.