Cybersecurity and Data Analytics

CACI•San Antonio, TX

13d

About The Position

Join a dynamic cybersecurity and data analytics team responsible for building and maintaining mission-critical data pipelines. Lead efforts to integrate vulnerability, event, and log data across ACAS, Elastic, and Splunk platforms. Support large-scale data environments that power real-time insights and automated security analytics. Collaborate with cross-functional teams to optimize data ingestion, storage, and visualization for operational efficiency. Contribute to data governance, standardization, and automation initiatives to strengthen organizational cybersecurity posture.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
3+ years of experience in data engineering, integration, or ETL pipeline development.
Proven experience with ACAS (Tenable/Nessus), Elastic Stack (Elasticsearch, Logstash, Kibana), and Splunk.
Strong proficiency in Python, PowerShell, or Bash for data manipulation and automation.
Hands-on experience with APIs, data connectors, and log ingestion frameworks.
Familiarity with SQL and NoSQL databases.
Experience working in secure, enterprise, or government network environments.
Strong understanding of data security, access control, and encryption principles.
Excellent analytical, troubleshooting, and communication skills.
Must be located in San Antonio, TX or willing to relocate.

Nice To Haves

Experience with cloud data integration (AWS, Azure, or GCP).
Knowledge of cybersecurity frameworks and vulnerability management processes.
Experience with data orchestration and visualization tools.
Relevant certifications (e.g., Splunk Certified Architect, Elastic Certified Engineer, or Tenable ACAS certification).

Responsibilities

Design, develop, and maintain ETL/ELT pipelines for ingesting and transforming data pipelines into ACAS, Elastic, and Splunk deployments within a cloud environment.
Integrate diverse data sources (network sensors, security tools, and log aggregators) into centralized analytics environments.
Manage data workflows, ensuring accuracy, consistency, and compliance with data management policies.
Implement data quality checks, normalization, and enrichment processes to enhance analytical outcomes.
Collaborate with cybersecurity teams to translate analytical requirements into scalable data solutions.
Optimize data ingestion performance and automate recurring data management tasks using scripting or orchestration tools.
Monitor, troubleshoot, and resolve data pipeline and integration issues across platforms.
Maintain data schemas, metadata, and documentation for cross-team visibility.
Ensure compliance with data security and privacy standards in all engineering processes.