28 results for Data Engineer in Washington, DC

Data Center Technician

Ashburn, VA
onsite
Temporary
30.4 - 35.2 USD / Hourly
We are looking for an experienced Data Center Technician to join our team in Ashburn, Virginia. In this role, you will play a critical part in managing and maintaining infrastructure installations, ensuring reliability and efficiency in operations. This is a long-term contract position that offers the opportunity to work on diverse projects and collaborate with various teams to deliver high-quality results. Responsibilities: • Oversee infrastructure installation requests from initiation through completion, ensuring all objectives are met. • Conduct certifications of network connections and peripherals prior to deployment. • Coordinate with contractors to manage power remediation projects and ensure Service Levels are consistently achieved. • Provide detailed project estimates, interpreting schematics and drawings, and documenting requirements through collaboration with IT and project management teams. • Handle the creation, approval monitoring, and closure of work tickets and TCMs. • Assist in rack-level capacity management and monitor infrastructure performance. • Participate in meetings related to infrastructure projects and provide input on ongoing initiatives. • Generate Root Cause Analysis reports for power issues and implement corrective measures. • Manage infrastructure installations, including power surveys, cabling setups, and new data center build-outs. • Oversee equipment procurement processes, including ordering materials, tracking purchase orders, and managing inventory.
2026-02-26T00:00:00Z

Software Engineer in Test (SDET) – Java (Backend)

Washington, DC
onsite
Temporary
50 - 55 USD / Hourly
Software Engineer in Test (SDET) – Java (Backend)Hybrid – Washington, DC Job SummaryWe’re hiring a Software Engineer in Test (SDET) who can write automation code in Java and owns the full backend testing lifecycle for modern service-based systems. This role is 100% backend (no UI/front-end testing) and focuses on validating microservices and APIs running in a containerized environment. You’ll work closely with engineering and product teams to identify risk early, build reliable automated coverage, and speak up when something isn’t ready.Responsibilities<ul><li>Build and maintain Java-based automated tests for backend services and APIs.</li><li>Execute and improve the end-to-end testing process (test planning, test execution, defect validation, regression).</li><li>Test microservices and distributed systems, including service-to-service behavior and integration points.</li><li>Validate REST APIs and troubleshoot issues through logs, debugging, and structured investigation.</li><li>Support performance testing using Gatling; expand/maintain performance suites as needed.</li><li>Collaborate with engineers and stakeholders to raise concerns, communicate risk, and drive quality decisions.</li><li>Work with internal tooling used for automation and testing (no required external framework experience—strong fundamentals matter most).</li><li>Contribute to quality improvements across deployments and releases in Kubernetes environments.</li></ul>
2026-02-16T00:00:00Z

Principal Advanced Analytics Engineer

Herndon, VA
onsite
Permanent
160000 - 180000 USD / Yearly
We are looking for an experienced Principal Advanced Analytics Engineer to join our team in Reston, Virginia. In this role, you will collaborate with business leaders and technical experts to design and implement cutting-edge AI and machine learning solutions that drive impactful insights and decision-making. This position offers the opportunity to lead advanced analytics initiatives, establish engineering standards, and mentor team members while staying at the forefront of emerging technologies. Responsibilities: • Collaborate with stakeholders to design and implement AI/ML solutions tailored to business objectives. • Develop and enforce engineering standards, design patterns, and quality controls for analytics projects. • Build and manage CI/CD pipelines for machine learning models, incorporating automated testing, monitoring, and retraining processes. • Integrate Responsible AI practices to ensure fairness, bias detection, explainability, and compliance with regulations. • Create and maintain enterprise data models, including dimensional and star schemas, to support analytics and business intelligence. • Work closely with analytics teams to deliver scalable and efficient data solutions. • Implement robust data security measures, access controls, and lineage tracking in line with corporate policies and privacy laws. • Stay updated on advancements in AI, ML, and BI technologies, bringing innovative solutions to the team. • Provide mentorship to Data Analytics Engineers, fostering attention to detail and promoting best practices.
2026-03-10T00:00:00Z