Data Engineer I Jobs in Washington (NOW HIRING)

• 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 DevSecOps 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 SageMaker 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 DevSecOps 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 tools such as Palantir MSS Workshop and Slate applications.
• Proficiency with Python, SQL, and distributed data frameworks, including technologies such as Spark, Databricks, and PySpark.
• Experience developing machine learning models from training through deployment using industry-standard tools and libraries such as scikit-learn, TensorFlow, and XGBoost.
• Strong technical communication skills with the ability to explain complex concepts to non-technical audiences.

• 4+ years of experience in applied data science, Palantir Foundry development, or data-pipeline development.
• Familiarity with MLOps, API development, and secure cloud-based environments, including AWS, Azure, or Palantir Foundry.
• Strong understanding of data validation, model testing, and performance-evaluation techniques.

Expression offers competitive salaries and benefits, such as:

• 401k matching

• PPO and HDHP medical/dental/vision insurance

• Education reimbursement

• Complimentary life insurance

• Generous PTO and holiday leave

• Onsite office gym access

• Commuter Benefits Plan