Security Data & Automation Engineer

Xcel Engineering•Oak Ridge, TN

3d•Onsite

About The Position

XCEL Engineering seeks a highly skilled Security Data & Automation Engineer to acquire and manage data, develop pipelines and ETL processes, automate workflows, integrate APIs, and build applications. The role uses Python and data engineering practices to develop scalable pipelines, integrate diverse data sources, support advanced AI capabilities, and ensure data is accurate, secure, and accessible for downstream analysis and operational use. The engineer will work with technical teams and stakeholders to identify requirements, improve data workflows, and deliver automation and integration solutions. The position is based in an inside office environment and involves prolonged computer use and possibly extended periods sitting at a desk. The environment is fast-paced and may involve extreme deadline pressures.

Requirements

U.S. citizenship and the ability to obtain and maintain a DoE security clearance.
Bachelor of Science degree in Information Technology, Computer Science, Data Engineering, Software Engineering, or a similar technical field.
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.
Demonstrated experience designing, developing, and maintaining data pipelines, ingestion workflows, and ETL processes.
Experience acquiring, transforming, validating, and integrating data from multiple sources, including databases, APIs, and file systems.
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.
Experience with data integration, ETL, or workflow automation tools such as Apache NiFi, Talend, Informatica, or similar platforms.
Familiarity with data processing and streaming technologies such as Kafka, Spark, or Hadoop.
Knowledge of secure data storage, data integrity, access controls, and applicable data governance requirements.
Experience troubleshooting complex data ingestion, integration, automation, and application development issues.
Strong analytical, problem-solving, and organizational skills, with the ability to translate technical requirements into effective solutions.
Excellent written and verbal communication skills and the ability to collaborate effectively across technical teams and stakeholder groups.
Ability to work independently, manage competing priorities, and deliver reliable, secure, and scalable technical solutions.

Nice To Haves

Experience supporting data engineering, automation, or application development in a government, defense, or other security-sensitive environment.
Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
Familiarity with orchestration frameworks, workflow automation platforms, and distributed data processing environments.
Experience integrating AI/ML capabilities into data pipelines, applications, or operational workflows.
Knowledge of AI inference workflows, model deployment, and hardware/software environments used to support AI capabilities.
Experience optimizing data pipeline performance, scalability, reliability, and resource utilization.
Familiarity with data security best practices, regulatory compliance, and enterprise data governance.
Experience developing custom integrations and automation solutions across complex enterprise systems.

Responsibilities

Identify, connect to, and acquire data from 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.
Design, implement, monitor, troubleshoot, and optimize ETL processes, automation workflows, and API integrations.
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.
Document data sources, ingestion processes, transformations, integrations, and workflows in accordance with established standards.
Ensure data engineering and automation solutions comply with applicable security, governance, and regulatory requirements.
Collaborate with technical teams and stakeholders to identify requirements, improve data workflows, and implement automation and integration solutions.
Communicate technical concepts, project updates, and solutions clearly to technical and non-technical stakeholders.