Vantage Cyber Staff Aug - Cybersecurity Data Engineer

Evolution Cloud Services (EVOCS)

19h•Remote

About The Position

As a Cybersecurity Data Engineer, you will design and maintain the data pipelines and integrations that power a single pane of glass across our clients' cybersecurity and IT tools. You will be responsible for turning fragmented, tool-level data into normalized, trusted models that fuel executive reporting, operational dashboards, and better security decisions.

Requirements

5+ years experience in data engineering for cybersecurity or IT operational environments
Experience with Microsoft Fabric, Azure Data Lake, Azure Data Factory, Databricks, Snowflake, or comparable data platforms
Security data normalization, correlation, enrichment, and reporting
Power BI semantic models, executive dashboards, and operational analytics
Integration with SIEM, vulnerability management, EDR, IAM, cloud security, ITSM, CMDB, and infrastructure monitoring platforms
Data governance, data quality management, lineage, cataloging, and access control
A passion for building the single source of truth that security and IT teams rely on
Ability to design data models that scale across multiple cybersecurity and IT source systems
An undying concern about data quality, lineage, and trust across every reporting pipeline
A willingness to partner closely with cybersecurity, IT, and analytics stakeholders
Strong interpersonal and communication skills -- this is a client-facing role that involves frequent interaction via email, calls, and meetings

Nice To Haves

A degree in Data Engineering, Computer Science, Information Systems, or a related field
Ability to lead source-system integration projects end-to-end

Responsibilities

Design, build, and maintain cybersecurity and applicable IT data pipelines that support centralized analytics and reporting
Integrate data from cybersecurity tools, IT platforms, vulnerability management systems, cloud platforms, identity systems, endpoint tools, and other applicable sources
Create a single pane of glass for cybersecurity and applicable IT data to improve visibility, decision-making, and operational prioritization
Normalize, enrich, correlate, and validate data across source systems to improve reporting consistency and trust in metrics
Develop clear data models that support executive reporting, operational dashboards, risk reporting, and trend analysis
Support data quality controls, lineage documentation, source mapping, ingestion monitoring, and repeatable data engineering standards
Partner with cybersecurity, IT, and analytics stakeholders to ensure dashboards and reports reflect actionable insight rather than disconnected tool-level reporting