This role pays less than
61%
of similar roles. Most pay
$150,000–$204,950
— the shaded band above.
At the midpoint, this role pays about
$161k
versus about
$177k
for comparable roles.
Based on 240 similar postings.
Employer
About State Street
State Street Corporation is one of the world''s largest custodian banks and asset managers, providing investment servicing, investment management, and investment research to institutional investors. Industry: Financial Services & Asset Custody
State Street currently has
176 open roles
on FindRole.
Listed pay typically runs
$120,000–$202,500
across 172 roles with salary data.
The Security Data Solutions Engineer joins the Cyber Data & Analytics team to develop advanced data platforms, intelligent automation, and AI-powered solutions for cybersecurity. This role bridges cybersecurity, data engineering, and product management to design and implement scalable security telemetry solutions across on-premises, cloud, and hybrid environments. You will serve as a subject matter expert for SIEM, threat hunting, and detection engineering while defining roadmaps and requirements for security data products. Key responsibilities include designing ingestion, transformation, and normalization pipelines for diverse sources like identity systems and network devices. The role requires expertise in Python, SQL, Spark, Kafka, Databricks, Snowflake, and Splunk, alongside experience with Cribl or OpenTelemetry. You will solve complex problems regarding log management and event correlation to improve detection capabilities while ensuring data quality and governance across cloud-native architectures like AWS, Azure, and Google Cloud.
Design and implement enterprise-scale security telemetry solutions across on-premises, cloud, and hybrid environments.
Define data requirements, success criteria, and roadmaps for security products in collaboration with stakeholders.
Develop scalable ingestion, transformation, enrichment, and normalization patterns for SIEM and cybersecurity platforms.
Analyze source systems and log schemas to establish onboarding and normalization strategies for diverse data sources.
Establish data quality metrics, service-level objectives, and governance controls for security data products.
Implement AI, automation, and self-service workflows to improve cybersecurity outcomes and reduce manual effort.
Lead cross-functional workshops to identify opportunities for improving cybersecurity visibility and operational efficiency.
Provide technical leadership for complex cybersecurity data integration and modernization initiatives.
What we're looking for
Bachelor’s degree in computer science, cybersecurity, engineering, data engineering, information systems, or a related technical field.
Master’s degree in computer science, cybersecurity, engineering, data science, or business administration is preferred.
Industry certifications such as CISSP, CISM, CCSP, Splunk, Microsoft Security, AWS, or Databricks are preferred.
8+ years of experience in cybersecurity, data engineering, AI/ML, security analytics, SIEM engineering, or product design.
5+ years of hands-on experience designing and implementing enterprise-scale data products, data lakes, and warehouse solutions.
Advanced expertise in Python, SQL, Spark, Kafka, Databricks, Snowflake, and cloud-native platforms to build scalable data pipelines.
Proven experience with SIEM platforms (Splunk, Sentinel, QRadar) and advanced knowledge of cybersecurity telemetry and detection engineering.
Demonstrated product management skills including roadmap development, feature prioritization, and stakeholder management in Agile or DevSecOps environments.