HUD - Data / Platform Engineer

Remote
Full Time
HUD - SOC
Experienced
cFocus Software seeks a Data / Platform Engineer to join our program supporting Housing and Urban Development (HUD). This position is remote. This position requires a Public Trust clearance.
Qualifications:
  • Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field.
  • 7+ years of experience in data engineering, platform engineering, or cloud engineering roles.
  • Experience with data pipeline tools (e.g., Kafka, Kinesis, Logstash, Fluentd).
  • Experience with SIEM platforms (e.g., Splunk) and log aggregation systems
Duties:
  • Design, build, and maintain data platforms supporting SOC operations, including log aggregation, analytics, and security data pipelines.
  • Engineer and optimize data ingestion pipelines for security telemetry (SIEM, EDR, cloud logs, network logs).
  • Develop and maintain scalable data architectures in AWS GovCloud and hybrid environments.
  • Support real-time and batch data processing for security monitoring and analytics.
  • Integrate data from multiple sources (cloud services, applications, endpoints, network devices, third-party platforms).
  • Ensure data quality, integrity, availability, and performance across platforms.
  • Implement centralized data lake or data warehouse solutions for security analytics.
  • Support SIEM/SOAR platforms through data normalization, enrichment, and correlation.
  • Develop dashboards, reporting solutions, and visualization tools for real-time security posture monitoring.
  • Automate data workflows and platform operations using scripting and orchestration tools.
  • Support compliance requirements by ensuring proper data retention, logging, and auditability.
  • Collaborate with SOC analysts and engineers to enable threat detection and response capabilities.
  • Optimize platform performance, scalability, and cost efficiency.
  • Implement monitoring, alerting, and observability for data pipelines and platforms.
  • Maintain documentation for data architecture, pipelines, and integrations.


 
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