AI-Ready Security Data & Automation Engineer

MartinFederal Consulting, LLC

Oak Ridge (TN)

On-site

USD 120,000 - 180,000

Full time

5 days ago

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Job summary

XCEL Engineering, Inc. seeks a Security Data & Automation Engineer with hands-on experience in data acquisition, pipeline development, ETL processes, automation, API integration, and application development.

Strong Python and data engineering background is required to design scalable pipelines and secure data management for downstream analysis. The role supports AI integration and secure data practices, collaborating with teams to deliver reliable, scalable technical solutions in an environment

Qualifications

U.S. Citizen with the ability to obtain and maintain a DoE security clearance.
Minimum 10 years of substantial progressive experience in data engineering, software development, automation, systems integration, or a related technical field.
Strong proficiency in Python for application development, scripting, data processing, and automation.
Experience designing, developing, and maintaining data pipelines, ingestion workflows, and ETL processes.
Experience developing and maintaining API integrations, automated workflows, and scalable data processing solutions.
Proficiency with Git-based development workflows, including version control and collaborative software development practices.

Responsibilities

Identify, connect to, and acquire data from diverse sources, including databases, APIs, file systems, and streaming platforms.
Design, develop, automate, and maintain scalable data pipelines and ingestion workflows.
Transform, clean, validate, parse, enrich, and convert raw data into reliable, usable formats.
Integrate data from multiple sources to create cohesive, accurate, and accessible datasets.
Develop and maintain custom applications, scripts, and automation tools using Python and Git-based development workflows.
Troubleshoot data ingestion, processing, workflow, and integration issues to ensure reliable performance and scalability.
Support advanced AI integration, including hardware and software deployment, inference workflows, and performance optimization.
Implement secure data storage and management practices to ensure data integrity, availability, and accessibility for downstream systems and users.
Document data sources, ingestion processes, transformations, integrations, and workflows in accordance with established standards.
Collaborate with technical teams and stakeholders to identify requirements, improve data workflows, and implement effective automation and integration solutions.