Cybersecurity Data Architect

• Partner with cybersecurity leaders, risk stakeholders, and cross-functional teams to define and deliver data-driven cybersecurity use cases aligned with enterprise risk frameworks such as NIST CSF.
• Design and implement scalable data pipelines, models, and architectures to support cybersecurity analytics, AI, reporting, and risk insights.
• Ingest, transform, normalize, and model security and IT datasets while ensuring data quality, lineage, and governance.
• Develop and deliver analytics products including dashboards, metrics, and operational reports for leadership and cybersecurity teams.
• Prototype and productionize integrations across cybersecurity tools and enterprise data platforms.
• Apply advanced analytics and automation techniques to convert raw cybersecurity data into actionable insights and risk indicators.
• Leverage AI-assisted tools and workflows to accelerate analytics, development, and experimentation within governance standards.
• Translate complex technical findings into clear, business-aligned insights for executive and non-technical stakeholders.
• Act as a technical advisor to shape cybersecurity data strategy, architecture, and future analytics capabilities.

• Bachelor s degree in Computer Science, Data Engineering, Information Security, or related field.
• 8+ years of experience in cybersecurity, risk, or technology domains with strong data engineering or data architecture expertise.
• Experience designing and building data pipelines, data models, and analytics architectures (batch and/or streaming).
• Hands-on experience with modern data platforms such as Databricks, Redshift, Snowflake, or similar.
• Strong knowledge of cybersecurity concepts including vulnerabilities, threats, controls, and risk management.
• Proficiency in programming languages such as Python and SQL.
• Experience working with data engineering and platform teams to ensure scalability and maintainability.
• Strong analytical and problem-solving skills with the ability to assess data feasibility and gaps., * Certifications such as CISSP, CISM, or equivalent cybersecurity credentials.
• Experience applying advanced analytics techniques such as predictive modeling, trend analysis, and risk indicators.
• Familiarity with AI-driven analytics or development tools in secure enterprise environments.
• Experience with BI and visualization tools such as Tableau or Power BI.
• Knowledge of cybersecurity frameworks such as NIST CSF and MITRE ATT&CK.
• Experience working with enterprise data ecosystems including data lakes and data warehouses.
• Proven ability to lead end-to-end data and analytics initiatives in cybersecurity environments.
• Strong consultative and leadership skills with experience influencing stakeholders.

Soft Skills:

• Excellent communication skills with the ability to translate technical insights into business context.
• Strong collaboration and stakeholder management abilities.
• Strategic thinking with a focus on risk-based decision making.
• Self-driven with the ability to work independently and lead initiatives.