Data Infrastructure Specialist

2 weeks ago

Makati City, National Capital Region, Philippines beBeeSecurity Full time ₱6,000,000 - ₱7,500,000
Job Title

We are seeking a skilled Security Data Engineer to drive the automation of our data pipelines, dashboards, and reporting infrastructure across diverse security data sources.

This critical role involves reducing manual effort, increasing data reliability, and delivering timely, actionable insights to security teams and stakeholders.

Key Responsibilities:
  • Automation & Engineering
    • Automate end-to-end data extraction, transformation, and loading (ETL) processes from various sources, including databases, APIs, and third-party tools.
    • Build and maintain scalable, fault-tolerant pipelines to collect, normalize, and enrich security data.
    • Develop event-driven and scheduled data workflows to ensure timely delivery of critical security metrics and insights.
    • Design automated classifiers, scoring systems, or recommendation engines to support threat detection, vulnerability management, or incident prioritization.
    • Utilize large language models (LLMs) or embeddings where appropriate to enrich and interpret semi-structured log data.
  • Reporting & Dashboards
    • Automate the generation and deployment of interactive dashboards and reports using tools like Apache Superset, Grafana, or similar.
    • Ensure reports are updated in near real-time and designed to scale with growing data volumes.
  • Analysis & Insights
    • Conduct exploratory data analysis to detect patterns, anomalies, and trends in security data.
    • Translate complex datasets into automated alerts, metrics, and recommendations that support incident response and threat detection.
  • Stakeholder Enablement
    • Collaborate with engineers, security teams, and internal stakeholders to identify manual reporting tasks that can be automated or streamlined.
    • Customize automation solutions to align with stakeholder needs and business goals.
  • Documentation & Governance
    • Maintain clear, version-controlled documentation of data sources, ETL pipelines, and automation logic.
    • Ensure automation processes meet internal security, compliance, and data governance standards.

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