Secure Data Engineer for AI & DoD Pipelines

Talentify; Arlington (VA); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

401k matching

Medical/dental/vision insurance

Education reimbursement up to $10,000/

Life insurance

PTO and holidays

Onsite gym facility

Commuter Benefits Plan

In-office Cold Brew

Job summary

Expression seeks an experienced Data Engineer to design, develop, and deploy scalable AI-enabled data solutions for DoD CDAO ADA IR program. You will work with cross-disciplinary teams to transform structured and unstructured data into actionable insights, with emphasis on reproducibility, testing, and secure deployment.

The role involves developing data pipelines, ML models, and services within CI/CD pipelines in secure environments, using Python, Spark, and cloud-native frameworks like

Qualifications

• Bachelor’s degree with 3+ years’ relevant experience or equivalent.
• Experience with data visualization and data storytelling using Palantir MSS Workshop and Slate.

Responsibilities

• Design, develop, and maintain reusable data services for ingestion, transformation, preprocessing, and feature engineering for AI/ML workflows.
• Build scalable data pipelines for structured and unstructured mission data.
• Develop ML-enabled capabilities and ensure secure production deployment.

Skills

Python

SQL

Spark

Databricks

PySpark

Palantir MSS Workshop

Slate

scikit-learn

TensorFlow

XGBoost

Education

Bachelor’s degree + 3 years of specialized experience

Associate’s degree + 7 years of specialized experience

Major certification + 7 years of specialized experience

11 years of specialized experience

Tools

Databricks

Docker

Terraform

Job description

Expression seeks an experienced Data Engineer to design, develop, and deploy scalable AI-enabled data solutions for DoD CDAO ADA IR program. You will work with cross-disciplinary teams to transform structured and unstructured data into actionable insights, with emphasis on reproducibility, testing, and secure deployment.

The role involves developing data pipelines, ML models, and services within CI/CD pipelines in secure environments, using Python, Spark, and cloud-native frameworks like