Data Engineer

Staffed4U; Chantilly (VA); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Competitive compensation

Medical, dental, vision coverage

401(k) with company contribution

Paid time off and holidays

Life and disability insurance

Professional development opportunities

Challenging mission-focused work

Job summary

Staffed4U in Chantilly, VA is seeking a Data Engineer to design, build, and optimize scalable data pipelines and architectures supporting analytics and machine learning. The role requires active TS/SCI with Full Scope Polygraph and is onsite for the initial 9–12 month mission-focused engagement.

You will work with Python, SQL, AWS, and modern data tooling to ingest, transform, and deliver clean datasets for stakeholders.

Qualifications

• 3–5+ years of professional experience in Data Engineering or a related technical field.
• Experience designing and implementing ETL/ELT pipelines.
• Experience processing and managing large-scale structured and unstructured datasets.
• Experience working in cloud-based data environments.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines for batch and real-time processing using Python and SQL.
• Integrate data from structured and unstructured sources (DBs, APIs, streaming platforms, PDFs, Office files).
• Build scalable data architectures to support analytics and ML workloads.
• Optimize data processing in AWS for performance, scalability, and cost efficiency.
• Prepare for feature engineering and ML model support with scalable pipelines.

Skills

Python

SQL

PySpark

AWS

REST APIs

Docker

Kubernetes

Git

ML workflows

Tools

ElasticSearch/OpenSearch

Neo4j

Job description

Location: Chantilly, VA
Work Schedule: Full-Time, Onsite
Clearance Required: Active TS/SCI with Full Scope Polygraph (FSP)
Employment Type: W-2

Position Overview

We are seeking a talented and mission-focused Data Engineer to join our growing team supporting cutting-edge intelligence community initiatives in Chantilly, VA. This role offers the opportunity to work with large-scale datasets and contribute to the development of a custom enterprise platform supporting critical mission objectives.

The selected candidate will play a key role in designing, building, and optimizing scalable data pipelines and architectures that support analytics, machine learning, and enterprise data integration efforts. This position is funded for an initial 9–12 month period aligned with defined mission deliverables and system development timelines, with all development performed onsite at the customer location.

Key Responsibilities

• Design, develop, and maintain ETL/ELT pipelines for both batch and real-time data processing using Python and SQL.
• Integrate data from a variety of structured and unstructured sources, including databases, APIs, streaming platforms, PDFs, and Microsoft Office files.
• Build scalable and maintainable data architectures to support analytics and machine learning workloads.
• Optimize data processing workflows and queries for performance, scalability, and cost efficiency within AWS environments.
• Support future pipeline scalability through exposure to PySpark and other distributed data processing frameworks.
• Develop and maintain web scraping and data ingestion workflows to collect and process open-source data.
• Transform collected information into structured datasets and visualizations for stakeholder analysis and decision-making.

Data Management & Optimization

• Collect, clean, validate, and manage large volumes of structured and unstructured data.
• Implement data quality controls, validation procedures, and version management practices.
• Design and optimize data storage solutions utilizing AWS S3 for raw, intermediate, and production datasets.
• Implement data governance best practices including documentation, cataloging, lineage tracking, and security controls.
• Ensure compliance with customer and security requirements for data management and handling.
• Partner closely with Data Scientists, Analysts, and Engineering teams to understand business and mission requirements.
• Prepare clean, structured, and feature-ready datasets for analytics and machine learning applications.
• Support feature engineering, aggregation, and large-scale data transformations.
• Assist with deploying machine learning models into production environments while supporting monitoring, versioning, and performance optimization.
• Integrate and consume REST APIs to support data acquisition and application workflows.
• Utilize Docker, Kubernetes, Git, and CI/CD pipelines to support deployment and operational workflows.

Documentation & Communication

• Document data pipelines, architectures, schemas, and transformation processes.
• Communicate technical concepts effectively to both technical and non-technical stakeholders.
• Participate in code reviews and promote engineering best practices across the team.
• Contribute to continuous improvement efforts related to data engineering, automation, and platform development.

Required Qualifications

Experience

• 3–5+ years of professional experience in Data Engineering or a related technical field.
• Experience designing and implementing ETL/ELT pipelines.
• Experience processing and managing large-scale structured and unstructured datasets.
• Experience working in cloud-based data environments.

Technical Skills

• Strong proficiency with Python and SQL.
• Experience with PySpark or other distributed processing frameworks (highly desired).
• Experience with ElasticSearch/OpenSearch technologies.
• Experience working within AWS cloud environments.
• Experience supporting Linux-based systems.
• Proficiency with Git for version control and collaborative development.
• Understanding of machine learning workflows and MLOps concepts.
• Experience integrating and consuming REST APIs.
• Familiarity with Docker, Kubernetes, and CI/CD pipelines.

Clearance Requirements

• Active TS/SCI with Full Scope Polygraph (FSP) is required.

Professional Skills

• Strong collaboration and communication skills.
• Ability to communicate complex technical concepts to non-technical audiences.
• Detail-oriented with a strong commitment to data quality and integrity.
• Ability to manage multiple priorities in a fast-paced mission environment.
• Strong analytical and problem-solving capabilities.

Desired Qualifications

• Hands-on experience with graph databases.
• Experience modeling, querying, and optimizing Neo4j databases.
• Experience supporting advanced analytics, knowledge graphs, or entity resolution systems.
• Experience working within Intelligence Community environments.

Why Join Us?

This is an opportunity to work alongside highly skilled engineers, analysts, and data scientists supporting critical national security missions. You'll have the chance to build scalable data solutions, support advanced analytics initiatives, and help shape the future of enterprise data systems in a dynamic and impactful environment.

• Competitive Compensation
• Comprehensive Medical, Dental, and Vision Coverage
• 401(k) with Company Contribution
• Paid Time Off and Company Holidays
• Life and Disability Insurance
• Professional Development Opportunities
• Challenging and Meaningful Mission-Focused Work

Equal Opportunity Employer

We are committed to fostering an inclusive workplace and welcome qualified applicants from all backgrounds. Employment decisions are made without regard to race, color, religion, sex, national origin, disability, veteran status, or any other protected characteristic.