{"schemaVersion":"jobsearcher.job.v1","id":"774b0bcc25dc3ae1e0e05ce5","url":"https://jobsearcher.com/jobs/774b0bcc25dc3ae1e0e05ce5","canonicalUrl":"https://jobsearcher.com/jobs/774b0bcc25dc3ae1e0e05ce5","title":"Data Engineer","description":"Expression is seeking an experienced Data Engineer to support the design, development, and operational deployment of scalable, AI-enabled data solutions for the Department of Defense CDAO ADA IR program.\n\nThe Data Engineer will work as part of a multidisciplinary team integrating data engineering, advanced analytics, machine learning, and software engineering capabilities into mission-critical environments supporting Combatant Commands. This role will design and deploy data pipelines, preprocessing workflows, feature-engineering strategies, reusable data services, and machine learning capabilities within secure, containerized environments.\n\nThe successful candidate will collaborate with product managers, full-stack developers, platform and DevSecOps engineers, data scientists, and mission stakeholders to transform structured and unstructured data into operational insights and decision-support capabilities. The role combines data engineering, applied data science, and production ML responsibilities and emphasizes reproducibility, testing, secure deployment, technical communication, and continuous delivery.\n\nClearance: Secret clearance required ability to obtain TS/SCI clearance\nLocation: Onsite Washington DC\n\nKey Responsibilities\n\nDesign, develop, and maintain reusable services for data ingestion, transformation, preprocessing, and feature engineering supporting AI/ML workflows.\nBuild scalable data pipelines and workflows supporting structured and unstructured mission data.\nImplement data science capabilities such as entity resolution, classification, clustering, prediction, anomaly detection, pattern recognition, and decision-support functions.\nDevelop services within secure, containerized environments using established CI/CD, version-control, testing, and documentation standards.\nCollaborate with DevSecOps engineers to integrate data and ML services into secure production environments using technologies such as Databricks, Docker, and Terraform.\nEnsure production services meet applicable performance, reliability, security, and architectural requirements for DoD enterprise and cloud-native environments.\nDevelop and deploy standalone and embedded machine learning models supporting mission decision-making, automation, anomaly detection, and pattern recognition.\nSelect and implement appropriate modeling approaches using Python, Spark, and cloud-native ML frameworks such as SageMaker and MLflow.\nMaintain reproducibility and interpretability of model outputs to support mission transparency and audit requirements.\nPackage model-inference services using documented APIs for integration with end-user applications, operational dashboards, and other mission capabilities.\nConduct exploratory data analysis to identify patterns, trends, data gaps, and opportunities across structured and unstructured datasets.\nDevelop data visualizations, analytical outputs, and interpretive summaries supporting stakeholder understanding and product-team decisions.\nTranslate analytical findings into actionable recommendations using visual, narrative, and quantitative communication methods.\nDevelop and contribute reusable analysis templates, queries, and analytical workflows to improve delivery efficiency.\nEngage product managers and mission users to define data, analytical, and model requirements aligned with operational objectives.\nCollaborate with software, platform, and DevSecOps engineers to ensure data science components align with technical constraints, architecture, and deployment patterns.\nParticipate in Agile sprint planning, retrospectives, demonstrations, and related delivery activities.\nMaintain documentation supporting technical accountability, reproducibility, operational handoff, and sustainment.\n\nRequired Qualifications\n\nOne of the following combinations of education, certification, and recent specialized experience:\nBachelor's degree plus 3 years of recent specialized experience; or\nAssociate's degree plus 7 years of recent specialized experience; or\nMajor certification plus 7 years of recent specialized experience; or\n11 years of recent specialized experience.\nExperience with data visualization and data storytelling using tools such as Palantir MSS Workshop and Slate applications.\nProficiency with Python, SQL, and distributed data frameworks, including technologies such as Spark, Databricks, and PySpark.\nExperience developing machine learning models from training through deployment using industry-standard tools and libraries such as scikit-learn, TensorFlow, and XGBoost.\nStrong technical communication skills with the ability to explain complex concepts to non-technical audiences.\n\nPreferred Qualifications\n\n4+ years of experience in applied data science, Palantir Foundry development, or data-pipeline development.\nFamiliarity with MLOps, API development, and secure cloud-based environments, including AWS, Azure, or Palantir Foundry.\nStrong understanding of data validation, model testing, and performance-evaluation techniques.\n\nBenefits:\n\nExpression offers competitive salaries and benefits, such as:\n\n401k matching\nPPO and HDHP medical/dental/vision insurance\nEducation reimbursement up to $10,000/yr\nComplimentary life insurance\nGenerous PTO and 11 days of holiday leave\nOnsite gym facility and trainer\nCommuter Benefits Plan\nIn-office Cold Brew Coffee\n\nAbout Expression:\n\nFounded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, AI/ML, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community. Expression's culture focuses on creating immediate and sustainable value for our clients via agile delivery of tailored solutions built through constant engagement with our clients. Expression was ranked #1 on the Washington Technology 2018's Fast 50 list of fastest-growing small business Government contractors and a Top 20 Big Data Solutions Provider by CIO Review.\n\nWe make sure to provide everyone with the tools and opportunities to grow while working on some of the newest technologies in the industry. We get excited about celebrating our professionals' milestones, accomplishments, promotions, overcoming challenges, and many other aspects that make an engaging collaborative environment.\n\nEqual Opportunity Employer/Veterans/Disabled\nExpression is an Equal Opportunity Employer. If you require a reasonable accommodation during the application or interview process, please submit your request to our Human Resources department through the application portal.","company":"Expression","rawCompany":"expression","city":"Arlington","state":"VA","isRemote":false,"isActive":false,"createdAt":"2026-08-22T10:55:04.380Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer","description":"Expression is seeking an experienced Data Engineer to support the design, development, and operational deployment of scalable, AI-enabled data solutions for the Department of Defense CDAO ADA IR program.\n\nThe Data Engineer will work as part of a multidisciplinary team integrating data engineering, advanced analytics, machine learning, and software engineering capabilities into mission-critical environments supporting Combatant Commands. This role will design and deploy data pipelines, preprocessing workflows, feature-engineering strategies, reusable data services, and machine learning capabilities within secure, containerized environments.\n\nThe successful candidate will collaborate with product managers, full-stack developers, platform and DevSecOps engineers, data scientists, and mission stakeholders to transform structured and unstructured data into operational insights and decision-support capabilities. The role combines data engineering, applied data science, and production ML responsibilities and emphasizes reproducibility, testing, secure deployment, technical communication, and continuous delivery.\n\nClearance: Secret clearance required ability to obtain TS/SCI clearance\nLocation: Onsite Washington DC\n\nKey Responsibilities\n\nDesign, develop, and maintain reusable services for data ingestion, transformation, preprocessing, and feature engineering supporting AI/ML workflows.\nBuild scalable data pipelines and workflows supporting structured and unstructured mission data.\nImplement data science capabilities such as entity resolution, classification, clustering, prediction, anomaly detection, pattern recognition, and decision-support functions.\nDevelop services within secure, containerized environments using established CI/CD, version-control, testing, and documentation standards.\nCollaborate with DevSecOps engineers to integrate data and ML services into secure production environments using technologies such as Databricks, Docker, and Terraform.\nEnsure production services meet applicable performance, reliability, security, and architectural requirements for DoD enterprise and cloud-native environments.\nDevelop and deploy standalone and embedded machine learning models supporting mission decision-making, automation, anomaly detection, and pattern recognition.\nSelect and implement appropriate modeling approaches using Python, Spark, and cloud-native ML frameworks such as SageMaker and MLflow.\nMaintain reproducibility and interpretability of model outputs to support mission transparency and audit requirements.\nPackage model-inference services using documented APIs for integration with end-user applications, operational dashboards, and other mission capabilities.\nConduct exploratory data analysis to identify patterns, trends, data gaps, and opportunities across structured and unstructured datasets.\nDevelop data visualizations, analytical outputs, and interpretive summaries supporting stakeholder understanding and product-team decisions.\nTranslate analytical findings into actionable recommendations using visual, narrative, and quantitative communication methods.\nDevelop and contribute reusable analysis templates, queries, and analytical workflows to improve delivery efficiency.\nEngage product managers and mission users to define data, analytical, and model requirements aligned with operational objectives.\nCollaborate with software, platform, and DevSecOps engineers to ensure data science components align with technical constraints, architecture, and deployment patterns.\nParticipate in Agile sprint planning, retrospectives, demonstrations, and related delivery activities.\nMaintain documentation supporting technical accountability, reproducibility, operational handoff, and sustainment.\n\nRequired Qualifications\n\nOne of the following combinations of education, certification, and recent specialized experience:\nBachelor's degree plus 3 years of recent specialized experience; or\nAssociate's degree plus 7 years of recent specialized experience; or\nMajor certification plus 7 years of recent specialized experience; or\n11 years of recent specialized experience.\nExperience with data visualization and data storytelling using tools such as Palantir MSS Workshop and Slate applications.\nProficiency with Python, SQL, and distributed data frameworks, including technologies such as Spark, Databricks, and PySpark.\nExperience developing machine learning models from training through deployment using industry-standard tools and libraries such as scikit-learn, TensorFlow, and XGBoost.\nStrong technical communication skills with the ability to explain complex concepts to non-technical audiences.\n\nPreferred Qualifications\n\n4+ years of experience in applied data science, Palantir Foundry development, or data-pipeline development.\nFamiliarity with MLOps, API development, and secure cloud-based environments, including AWS, Azure, or Palantir Foundry.\nStrong understanding of data validation, model testing, and performance-evaluation techniques.\n\nBenefits:\n\nExpression offers competitive salaries and benefits, such as:\n\n401k matching\nPPO and HDHP medical/dental/vision insurance\nEducation reimbursement up to $10,000/yr\nComplimentary life insurance\nGenerous PTO and 11 days of holiday leave\nOnsite gym facility and trainer\nCommuter Benefits Plan\nIn-office Cold Brew Coffee\n\nAbout Expression:\n\nFounded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, AI/ML, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community. Expression's culture focuses on creating immediate and sustainable value for our clients via agile delivery of tailored solutions built through constant engagement with our clients. Expression was ranked #1 on the Washington Technology 2018's Fast 50 list of fastest-growing small business Government contractors and a Top 20 Big Data Solutions Provider by CIO Review.\n\nWe make sure to provide everyone with the tools and opportunities to grow while working on some of the newest technologies in the industry. We get excited about celebrating our professionals' milestones, accomplishments, promotions, overcoming challenges, and many other aspects that make an engaging collaborative environment.\n\nEqual Opportunity Employer/Veterans/Disabled\nExpression is an Equal Opportunity Employer. If you require a reasonable accommodation during the application or interview process, please submit your request to our Human Resources department through the application portal.","datePosted":"2026-08-22T10:55:04.380Z","dateModified":"2026-08-22T10:55:04.380Z","hiringOrganization":{"@type":"Organization","name":"Expression","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Arlington","addressRegion":"VA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"774b0bcc25dc3ae1e0e05ce5"},"url":"https://jobsearcher.com/jobs/774b0bcc25dc3ae1e0e05ce5"}}