Role Overview:

The Cyber Data Architect / Modeler is responsible for designing, governing, and evolving the enterprise cybersecurity data model that underpins reporting, analytics, and AI/ML initiatives. This role ensures that cyber data is well-modeled, secure, lineage-enabled, performant, and compliant, from ingestion through semantic presentation. The ideal candidate brings strong expertise in enterprise data modeling, Power BI semantic layers, SQL optimization, and cloud data platforms, with deep experience operating in cybersecurity or regulated environments. This role works closely with data engineering, BI, security, and governance teams to ensure data assets are fit for enterprise reporting and audit readiness.

Key Responsibilities:

Semantic Modeling & Enterprise Reporting Architecture:

- Design, develop, and maintain Power BI semantic models, datasets, and dataflows that support enterprise-wide cybersecurity reporting and analytics.

- Ensure semantic layers provide consistent, certified metrics and dimensions for executive, operational, and analytical use cases.

- Align semantic models with enterprise business definitions, cyber KPIs, and governance standards.

Power BI Governance & Standards:

- Define and enforce best practices for Power BI assets, including:

1. Dataset versioning and lifecycle management

2. Workspace structure and separation of duties

3. Row-Level Security (RLS) and access control design

4. Refresh strategies and scheduling

5. Enterprise-certified datasets and shared semantic models

- Ensure BI architecture supports scalability, security, and self-service analytics without compromising control.

Data Modeling & SQL Optimization:

- Develop and optimize SQL views, stored procedures, and transformation logic to support analytical and reporting workloads.

- Apply dimensional, relational, and hybrid modeling techniques to support high-performance query patterns.

- Partner with data engineering teams to ensure upstream transformations align with downstream analytical needs.

Data Lineage, Documentation & Metadata:

- Ensure end-to-end data lineage documentation is complete, accurate, and maintained across ingestion, transformation, and reporting layers.

- Define standards for metadata capture, model documentation, and traceability to support audits, impact analysis, and change management.

- Act as a steward for semantic and analytical data assets.

Enterprise Data Platform (EDP) Architecture:

- Architect data ingestion and transformation pipelines within the Enterprise Data Platform (EDP), such as:

1. Azure Data Lake

2. Databricks

3. Internal enterprise data platforms

- Define and document standards for structured, semi-structured, and unstructured data storage, including zoning strategies (raw, curated, gold).

- Ensure curated and gold layers are designed to meet enterprise cybersecurity reporting requirements.

Asset Design & Reporting Readiness:

- Ensure all data assetsincluding tables, curated datasets, gold layers, and semantic modelsare purpose-built to support:

1. Cybersecurity metrics and KPIs

2. Operational dashboards

3. Risk and compliance reporting

- Validate that data models meet performance, usability, and governance expectations before enterprise consumption.

Security, Compliance & Audit Support:

- Lead and support audits, compliance requests, and security reviews by:

1. Ensuring accurate data classification

2. Enforcing access management and least-privilege principles

3. Providing lineage, documentation, and usage evidence

- Partner with security, risk, and governance teams to align data architecture with frameworks such as NIST, ISO, SOC 2, or industry regulations.

Required Qualifications:

- Bachelors or Masters degree in Computer Science, Information Systems, Data Architecture, Cybersecurity, or a related field.

- 8+ years of experience in data architecture, data modeling, or analytics engineering roles.

- Deep hands-on experience with Power BI semantic models, enterprise datasets, and governance patterns.

- Advanced proficiency in SQL and analytical data modeling techniques.

- Experience designing data architectures on enterprise or cloud data platforms.

- Strong documentation, communication, and cross-functional collaboration skills.

Cybersecurity & Regulated Environment Experience (Critical):

- Experience supporting cybersecurity, risk, or compliance analytics in enterprise or regulated environments.

- Familiarity with security telemetry, operational metrics, and cyber reporting requirements.

- Understanding of data classification, access control, auditability, and secure reporting practices.

- Experience operating within governance frameworks such as NIST, ISO, SOC, or similar.

Preferred / Nice-to-Have Qualifications:

- Experience with Azure Data Lake, Databricks, or equivalent EDP technologies.

- Familiarity with metadata management and lineage tooling.

- Experience supporting SOC, GRC, or cyber risk reporting platforms.

- Power BI or data architecture certifications.

- Prior experience defining enterprise data standards or reference architectures.