Principal Engineer - Cyber Data and Engineering

Wells Fargo•Iselin, NJ

3d•Hybrid

About The Position

About this role: Wells Fargo is seeking a Principal Engineer to serve as the technical authority for Graph technologies as part of our Cyber Data Strategy. This role is responsible for designing, building, and scaling graph‑based data platforms that power deep analytics, advanced threat detection, and rapid cyber response across Vulnerability Management, Application Security, Cloud Security, and other Cyber Defense domains. This individual will lead the technical vision and execution for graph data modeling, large‑scale graph implementations, and advanced analytics use cases. Acting as the enterprise Subject Matter Expert (SME), the Principal Engineer will guide engineering teams at scale by defining reference architectures, design patterns, and best practices, while also executing hands-on proofs of concept to rapidly validate and evolve solutions. In this role, you will: Graph Architecture & Technical Strategy Define and own the Graph Technology strategy within the Cyber Data ecosystem, aligning with enterprise data and security architectures Design large‑scale graph data models representing complex cyber relationships such as assets, identities, vulnerabilities, configurations, threats, and attack paths Establish reference architectures and reusable design patterns for graph platforms supporting analytics, traversal, correlation, and inference Evaluate, recommend, and influence graph platforms and tooling (e.g., property graphs, RDF, cloud‑native graph services) through build vs. buy assessments Engineering Execution & Proof of Concepts Lead hands-on engineering efforts to implement scalable graph solutions, including rapid proofs of concept (POCs) for emerging threat scenarios and analytics use cases Partner with data and platform engineering teams to integrate graph data stores with existing data pipelines, analytics platforms, and observability tooling Drive performance, scalability, and reliability optimizations for large, high‑volume graph datasets Ensure graph solutions meet enterprise requirements for security, resiliency, data quality, and operational excellence Advanced Analytics & Cyber Use Cases Enable advanced analytics use cases such as attack path analysis, blast radius modeling, threat correlation, entity resolution, and risk prioritization using graph technologies Collaborate with Cyber domain leaders, detection engineers, and data scientists to translate threat vectors into actionable graph‑based insights Influence how Cyber teams consume graph insights to detect threats earlier, reduce mean time to respond (MTTR), and improve proactive defense Technical Leadership & Influence Serve as the go‑to technical authority for graph technologies across Cyber Engineering and Data communities Guide multiple engineering teams through design reviews, architectural decisions, and technical problem-solving without direct managerial authority Mentor senior and staff engineers, raising the technical bar across the organization Clearly articulate technical concepts, trade‑offs, and architecture decisions to senior engineering leaders and executive stakeholders

Requirements

7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
7+ years of hands‑on software or data engineering experience, with significant depth in distributed systems or data platforms
3+ years of deep expertise designing and implementing graph technologies at scale
Proven experience operating as a technical lead or principal‑level engineer influencing architecture across multiple teams

Nice To Haves

Deep expertise in graph databases and frameworks (e.g., Neo4j, TigerGraph, JanusGraph, Amazon Neptune, Azure Cosmos DB Graph, or equivalent)
Strong experience designing complex graph data models for large, highly connected datasets
Familiarity with graph query languages (Cypher, Gremlin, SPARQL)
Experience building graph‑powered analytics for cybersecurity, risk, fraud, or complex domain modeling
Strong knowledge of cloud‑native architectures (Azure, AWS, GCP) and data platform integration
Experience integrating graph data with streaming, batch, and analytics platforms
Solid grounding in secure software development lifecycle (SSDLC) and enterprise risk expectations
Exceptional ability to influence without authority and operate effectively in large, matrixed organizations
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field; advanced certifications are a plus

Responsibilities

Graph Architecture & Technical Strategy Define and own the Graph Technology strategy within the Cyber Data ecosystem, aligning with enterprise data and security architectures Design large‑scale graph data models representing complex cyber relationships such as assets, identities, vulnerabilities, configurations, threats, and attack paths Establish reference architectures and reusable design patterns for graph platforms supporting analytics, traversal, correlation, and inference Evaluate, recommend, and influence graph platforms and tooling (e.g., property graphs, RDF, cloud‑native graph services) through build vs. buy assessments
Engineering Execution & Proof of Concepts Lead hands-on engineering efforts to implement scalable graph solutions, including rapid proofs of concept (POCs) for emerging threat scenarios and analytics use cases Partner with data and platform engineering teams to integrate graph data stores with existing data pipelines, analytics platforms, and observability tooling Drive performance, scalability, and reliability optimizations for large, high‑volume graph datasets Ensure graph solutions meet enterprise requirements for security, resiliency, data quality, and operational excellence
Advanced Analytics & Cyber Use Cases Enable advanced analytics use cases such as attack path analysis, blast radius modeling, threat correlation, entity resolution, and risk prioritization using graph technologies Collaborate with Cyber domain leaders, detection engineers, and data scientists to translate threat vectors into actionable graph‑based insights Influence how Cyber teams consume graph insights to detect threats earlier, reduce mean time to respond (MTTR), and improve proactive defense
Technical Leadership & Influence Serve as the go‑to technical authority for graph technologies across Cyber Engineering and Data communities Guide multiple engineering teams through design reviews, architectural decisions, and technical problem-solving without direct managerial authority Mentor senior and staff engineers, raising the technical bar across the organization Clearly articulate technical concepts, trade‑offs, and architecture decisions to senior engineering leaders and executive stakeholders