Cybersecurity Data Engineering Manager

Capital Group•Charlotte, NY

2d•Hybrid

About The Position

The Cybersecurity Engineering / Data Science Manager is a leader responsible for defining and executing the cybersecurity analytics, security data engineering, and security intelligence strategy for the organization. This role combines deep expertise in cybersecurity, data engineering, analytics, and cloud-native data platforms with strong people leadership and program management capabilities. This role places significant emphasis on SIEM engineering and operating enterprise-scale security data pipelines, data models, dashboards, managing dta ingestion and integration frameworks, and building advanced analytics and reporting to reduce risk to the firm. The manager leads a team of cybersecurity data scientists, data engineers and security engineers responsible for transforming security telemetry, operational data, threat intelligence, vulnerability data, cloud security signals, identity data, and business context into actionable intelligence to enable data driven decisions.

Requirements

Proven leader of data scientists, data engineers, or security data professionals.
Demonstrated ability to lead large, complex programs with significant organizational impact.
Strong stakeholder influence and consensus-building with senior leadership.
Deep knowledge of cybersecurity principles, cyber risk measurement, security operations, threat detection, vulnerability management, cloud security, and security telemetry.
Expertise in statistical modeling, machine learning, predictive analytics, anomaly detection, and behavioral analytics.
Strong understanding of cybersecurity KPIs, KRIs, operational metrics, and risk analytics frameworks.
Deep expertise building large-scale data pipelines, streaming architectures, and data integration platforms.
Extensive experience designing security-focused data models and analytical data structures.
Experience managing enterprise-scale security telemetry and observability platforms.
Strong understanding of data governance, metadata management, lineage, quality management, and regulatory requirements.
Expertise in cloud-native data architectures and modern data platform design.
Proficiency in Python and SQL.
Experience with cloud native technologies AWS, Snowflake, Databricks, or similar.
Experience with observability technologies like Cribl, Fluentd, OTEL or similar.
Experience with dashboarding and visualization technologies.
Strong understanding of cloud infrastructure, distributed computing, and enterprise-scale analytics environments.
Experience with building and managing security data platforms such as SIEM, security data lakes, observability platforms, and threat intelligence systems.
12+ years of experience in cybersecurity analytics, data science, data engineering, security operations, or related disciplines.
A Bachelor’s degree in Cybersecurity, Computer Science, or a related field.
5+ years leading technical teams.
Experience building security data lakes and enterprise-scale security analytics platforms.
Experience supporting AI-enabled security initiatives and cyber risk measurement programs.
Experience supporting executive reporting, regulatory examinations, and audit requirements.

Responsibilities

Defining and executing the cybersecurity analytics, security data engineering, and security intelligence strategy.
Leading a team of cybersecurity data scientists, data engineers and security engineers.
Transforming security telemetry, operational data, threat intelligence, vulnerability data, cloud security signals, identity data, and business context into actionable intelligence.
Enabling data-driven decisions.
SIEM engineering and operating enterprise-scale security data pipelines, data models, dashboards.
Managing data ingestion and integration frameworks.
Building advanced analytics and reporting to reduce risk to the firm.