Lead Data Engineer

About this role: Wells Fargo is seeking a Lead Data Engineer Engineer in Technology as part of Cybersecurity. Learn more about the career areas and lines of business at wellsfargojobs.com. Wells Fargo is seeking a Lead Data Engineer to join the Enterprise Services Technology (EST) Cyber Security organization. This role will help drive the evolution of enterprise data platforms supporting cybersecurity, technology risk, governance, analytics, reporting, AI-enabled services, and enterprise workflow capabilities. The ideal candidate will possess strong expertise in enterprise data engineering, large-scale ETL/ELT development, cloud-native technologies, event-driven architectures, and modern data integration patterns. This individual will serve as a technical leader responsible for designing scalable, secure, and resilient data solutions that support critical cybersecurity and enterprise technology functions across Wells Fargo. In this role, you will: Lead the design and implementation of enterprise-scale data platforms and solutions. Design and develop scalable data ingestion, transformation, enrichment, and distribution frameworks. Build and optimize high-performance ETL/ELT pipelines supporting operational, analytical, and regulatory workloads. Design and maintain enterprise data models, data architecture standards, and integration frameworks. Develop and support event-driven data processing solutions using streaming and messaging technologies. Create and optimize SQL-based solutions for analytics, reporting, troubleshooting, and operational processing. Partner with cybersecurity, technology risk, architecture, engineering, and business teams to deliver strategic data capabilities. Support advanced analytics, AI-enabled services, and enterprise reporting solutions through well-architected data services. Lead technical design activities, architecture reviews, and engineering best practices. Research and resolve complex production issues while ensuring platform stability, scalability, and performance. Mentor and provide technical guidance to data engineers throughout the development lifecycle. Drive continuous improvement in data engineering standards, automation, and operational excellence. Demonstrate proficiency in using AI‑assisted development and analysis tools (e.g., GitHub Copilot and approved code‑centric agents) Leverage AI to accelerate system design, coding, testing, analysis, and troubleshooting Apply strong technical judgment when validating and integrating AI‑assisted outputs into solutions Understand and account for model limitations, security risks, and operational considerations Apply AI responsibly in development and production environments Ensure AI usage aligns with security, compliance, privacy, and ethical standards Required Qualifications: 5+ years of Database Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Strong expertise in data modeling, data architecture, and enterprise data integration patterns. Strong experience developing and optimizing complex SQL queries and database solutions. Experience building scalable ETL/ELT pipelines and data ingestion frameworks. Experience integrating with ServiceNow and enterprise workflow platforms.

Experience supporting Cyber Security, Technology Risk, Governance, Risk & Compliance (GRC), or Enterprise Technology initiatives. Experience designing and supporting cybersecurity, asset inventory, operational reporting, or technology risk data solutions. Experience building enterprise reporting, analytics, and data consumption solutions. Experience deploying and supporting solutions on OpenShift (OCP), Kubernetes, or similar container platforms. Experience implementing data governance, metadata management, data lineage, and audit capabilities. Experience working with NoSQL databases, graph databases, Redis, or distributed caching