AI-Driven Security Data Platform Engineer

State Street

Princeton (NJ)

Hybrid

USD 120,000 - 203,000

Full time

13 days ago

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Job summary

State Street’s Cyber Data & Analytics (CyberDNA) team seeks a Security Data Solutions Engineer to shape next-gen cybersecurity data, analytics, and AI-powered solutions. Partnering with Global Cyber Security, Infrastructure, and Enterprise Continuity Services, the role designs scalable data platforms and automation to enable faster AI-driven decisions.

The ideal candidate bridges security data requirements with business objectives, delivering production-scale designs and data solutions that

Qualifications

Bachelor’s degree in computer science, Cybersecurity, Information Technology, Engineering, Data Engineering, Information Systems, or a related technical discipline.
8+ years of experience in cybersecurity, data engineering, AI/ML, security analytics, SIEM engineering, product design, or related technical fields.
5+ years of hands-on experience designing and implementing enterprise-scale data products, data lakes, Lakehouse and data warehouse solutions.
Advanced expertise in Python, SQL, Spark, Kafka, Databricks, Snowflake and cloud-native data platforms to design, build, and optimize scalable batch and real-time data pipelines.
Industry certifications such as CISSP, CISM, CCSP, Splunk Certified Architect, Splunk Certified Consultant, Microsoft Security Certifications, AWS Certifications, Databricks Certifications, or equivalent.
Experience delivering cybersecurity data products within highly regulated industries such as financial services, healthcare, or critical infrastructure.
Experience supporting AI/ML, Security Lakehouse, Agentic AI, Security Copilot, or advanced cyber analytics initiatives.

Responsibilities

Serve as the SME for security data solutions supporting SIEM, Analytics, Detection Engineering, Threat Hunting, and AI-enabled cybersecurity use cases.
Define data requirements, success criteria, onboarding priorities, roadmaps, and measurable outcomes for security data products.
Design and implement enterprise-scale security telemetry for on-prem, cloud, SaaS, and hybrid environments.
Analyze source systems, log schemas, metadata requirements, retention needs, and downstream analytics requirements to define onboarding and normalization strategies.
Design workflows for onboarding of security data from applications, cloud platforms, identity systems, infrastructure, network devices, databases, endpoints, and security tools.
Design scalable ingestion, routing, transformation, enrichment, normalization, and validation patterns for SIEM and cybersecurity data platforms.
Ensure security telemetry meets requirements for quality, completeness, timeliness, consistency, governance, and operational reliability.
Collaborate with architects, engineers, and product managers to prioritize capabilities and deliver solutions that align with cybersecurity and business objectives.
Working with Product managers, define product roadmaps, feature requirements, user stories, acceptance criteria, and delivery milestones for security data initiatives.
Lead cross-functional workshops with business and technical stakeholders to identify opportunities for improving cybersecurity visibility and operational efficiency.
Establish data quality metrics, service-level objectives, operational KPIs, data governance and process governance controls for security data products
Spearhead the implementation of AI, automation, and self-service workflow capabilities that improve cybersecurity outcomes and reduce operational effort.
Influence strategic direction of cybersecurity data platforms, data engineering processes, and analytics capabilities.
Provide technical leadership for complex cybersecurity data integration and modernization initiatives.