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# Data Engineer

- **Company:** TALENTOPS LLC
- **Location:** Chantilly, VA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Amazon S3, Big Data, Code Review, Databases, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Web Scraping, Data Integrity, Extract Transform Load (ETL), Graph Database, Python (Programming Language), Linux System Administration, Machine Learning, Microsoft Office, Neo4j, Open Source Technology, Performance Tuning, SQL Databases, Data Streaming, Unstructured Data, Management of Software Versions, Data Processing, Data Storage Technologies, Feature Engineering, Data Ingestion, Git, Pyspark, Kubernetes, Data Management, Machine Learning Operations, Restful APIs, Stream Processing, Data Pipelines, OpenSearch, Docker
- **Published:** October 22, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9255370/data-engineer

## About the Role

The ideal candidate has strong experience with Python, SQL, AWS, and data pipeline development and is comfortable working with both structured and unstructured data. Experience with PySpark, Elastic/OpenSearch, graph databases, and machine learning workflows is highly desirable., * Active TS/SCI with Full-Scope Polygraph.

 * 3-5+ years of professional experience in data engineering or a related technical role.
 * Strong experience with Python and SQL for data processing and pipeline development.
 * Experience working with AWS cloud services, particularly AWS S3.
 * Experience working in Linux environments.
 * Experience using Git for version control and collaborative development.
 * Strong understanding of ETL/ELT concepts and data pipeline architecture.
 * Ability to work effectively with Data Scientists, Analysts, Engineers, and other technical stakeholders.
 * Ability to communicate complex technical concepts to both technical and non-technical audiences.
 * Strong attention to detail with an emphasis on data quality and reliability.
 * Ability to manage multiple priorities in a fast-paced environment.

Highly Desired Technical Skills

 * PySpark or other big-data processing frameworks.
 * Elastic/OpenSearch for search and analytics.
 * Understanding of machine learning workflows and MLOps concepts.
 * Experience with Docker and Kubernetes.
 * Experience developing web scraping and open-source data ingestion solutions.

Desired Qualifications

 * Hands-on experience modeling, querying, and optimizing graph databases.
 * Experience with Neo4j is highly desired.
*

## Description

We are seeking a Data Engineer to join a growing team supporting cutting-edge work in the national security mission space. This role will focus on structuring, processing, and integrating large volumes of complex data into a custom-developed enterprise system., * Design, develop, and maintain ETL/ELT pipelines for batch and real-time data processing using Python and SQL.

 * Integrate data from multiple sources, including databases, APIs, streaming platforms, PDFs, Microsoft Office files, and open-source data.
 * Develop web scraping and data ingestion workflows to collect and transform open-source information into structured datasets.
 * Build scalable data architectures supporting analytics and machine learning workloads.
 * Collect, clean, validate, and transform large volumes of structured and unstructured data.
 * Design and optimize data storage within AWS S3, including raw, intermediate, and final datasets.
 * Optimize data processing and queries for performance and cost efficiency.
 * Implement data quality checks, version tracking, and processes to ensure data reliability.
 * Support data governance efforts, including documentation, cataloging, lineage, and security.
 * Ensure data handling and workflows comply with applicable security standards.

Data Science & ML Support

 * Partner closely with Data Scientists, Analysts, Engineers, and mission stakeholders to understand data requirements.
 * Prepare clean, structured, and feature-ready datasets for analytics and machine learning.
 * Support feature engineering, aggregations, and large-scale data transformations.
 * Assist with deploying ML models into production environments, including monitoring, versioning, and performance optimization.
 * Support scalable pipeline development using PySpark or similar big-data frameworks.

APIs, Containers & CI/CD

 * Integrate data and applications through REST APIs.
 * Utilize Docker, Kubernetes, Git, and CI/CD pipelines to deploy and manage data workflows.
 * Participate in code reviews and promote engineering and data-management best practices across the team.