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# Cleared Data Engineer (5786)

- **Company:** SMX, LLC
- **Location:** Montgomery, AL, United States
- **Experience:** Expert
- **Salary:** $115,000.0 - $187,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software Code Optimization, Encodings, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Migration, Data Stores, Data Systems, Database Applications, DevOps, Raw Data, Software Engineering, SQL Databases, Backend, Event Driven Architecture, Information Technology, Machine Learning Operations, Stream Processing, Data Pipelines, Vectorization, Databricks
- **Published:** October 30, 2026
- **Apply:** https://dejobs.org/x/x/E4AB156356C343C2A7A2902DFD9FC013/job/

## About the Role

* Bachelor's degree in computer science, - Information Technology, Data Engineering, or a related field.
 * 8 years of professional experience in a data engineering or backend software engineering role.
 * Active Secret security clearance.
 * Strong proficiency in SQL and data query creation.
 * Experience with data modeling, data migration, and ETL functions.
 * Excellent communication skills, both written and verbal, with the ability to interface with customers

Desired Skills & Experience

 * Experience supporting AI/ML pipelines, vectorization, or embedding generation
 * Experience with data governance, access controls, or sensitive data protection
 * Exposure to DevOps/CI-CD patterns for data workflows
 * Experience with Databricks
 * Experience with real-time data streaming and event-driven architectures

## Description

SMX is hiring a Data Engineer to design, build, and optimize systems for data collection, storage, access, and analytics at scale

The ideal candidate will analyze and organize raw data, build robust data systems, and explore ways to enhance data quality and reliability. This role involves collaborating with analytics and business teams to transform raw information from different sources into high-quality, accessible data pipelines.

 * Create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers
 * Make data available, accessible, and secure to stakeholders.
 * Ensure data pipelines meet Service Level Agreements and performance standards
 * Monitor data repositories and data pipelines to ensure operational efficiency and take action to address and resolve problems
 * Implement orchestration and automation solution for data pipelines