Data Engineer

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.

The 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.

The successful candidate will collaborate with product managers, full-stack developers, platform and Dev Sec Ops  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.

Clearance: Secret clearance required ability to obtain TS/SCI clearance
Location: Onsite Washington DC

• Design, develop, and maintain reusable services for data ingestion, transformation, preprocessing, and feature engineering supporting AI/ML workflows.
• Build scalable data pipelines and workflows supporting structured and unstructured mission data.
• Implement data science capabilities such as entity resolution, classification, clustering, prediction, anomaly detection, pattern recognition, and decision-support functions.
• Develop services within secure, containerized environments using established CI/CD, version-control, testing, and documentation standards.
• Collaborate with Dev Sec Ops  engineers to integrate data and ML services into secure production environments using technologies such as Databricks, Docker, and Terraform.
• Ensure production services meet applicable performance, reliability, security, and architectural requirements for DoD enterprise and cloud-native environments.
• Develop and deploy standalone and embedded machine learning models supporting mission decision-making, automation, anomaly detection, and pattern recognition.
• Select and implement appropriate modeling approaches using Python, Spark, and cloud-native ML frameworks such as Sage Maker and MLflow.
• Maintain reproducibility and interpretability of model outputs to support mission transparency and audit requirements.
• Package model-inference services using documented APIs for integration with end-user applications, operational dashboards, and other mission capabilities.
• Conduct exploratory data analysis to identify patterns, trends, data gaps, and opportunities across structured and unstructured datasets.
• Develop data visualizations, analytical outputs, and interpretive summaries supporting stakeholder understanding and product-team decisions.
• Translate analytical findings into actionable recommendations using visual, narrative, and quantitative communication methods.
• Develop and contribute reusable analysis templates, queries, and analytical workflows to improve delivery efficiency.
• Engage product managers and mission users to define data, analytical, and model requirements aligned with operational objectives.
• Collaborate with software, platform, and Dev Sec Ops  engineers to ensure data science components align with technical constraints, architecture, and deployment patterns.
• Participate in Agile sprint planning, retrospectives, demonstrations, and related delivery activities.
• Maintain documentation supporting technical accountability, reproducibility, operational handoff, and sustainment.

• One of the following combinations of education, certification, and recent specialized experience:
  • Bachelor’s degree plus 3 years of recent specialized experience; or
  • Associate’s degree plus 7 years of recent specialized experience; or
  • Major certification plus 7 years of recent specialized experience; or
  • 11 years of recent specialized experience.
• Experience with data visualization and data storytelling using…