Data Engineer

About this role: Wells Fargo is seeking a Data Engineer in Cybersecurity as part of Identity Access Management. Learn more about career areas and business divisions at wellsfargojobs.com The Data Engineer will support engineering efforts for cybersecurity identity and access management (IAM). This role sits at the intersection of cybersecurity, data engineering and data science, and is critical to enabling real-time, high-quality insights that support IAM operations, compliance, and executive decision-making. In this role, you will: Apply knowledge of statistical and data science methods and techniques to business problems relating to Identity and Access Management Develop and evaluate machine learning models using classification, clustering, and unsupervised learning techniques Partner with other IAM team members including operations, onboarding, initiatives and engineering teams as well as line of business and lines of defense teams to understand analytical needs and translate them into technical solutions. Assist in the design, support and operation of data pipelines, data models, dashboards, and API integrations to deliver real-time and batch analytics use cases. Apply established engineering and analytical best practices when developing solutions Develop solutions in accordance with established security, privacy, model risk, and regulatory guidelines Contribute to the development, testing, deployment, and support of ML-enabled analytical solutions under the guidance of senior engineers and data scientists. Assist in monitoring model health, reliability, and drift to ensure continuous improvement and required remediation Present recommendations for resolving more complex data management situations and exercise independent judgment while developing expertise in the business data policies, procedures and compliance requirements Collaborate and consult with technology colleagues, internal partners and stakeholders, including internal and external customers if applicable 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: 2+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Engineering, or related field. Strong SQL skills and ability to work with relational and analytical databases. Experience with Python data science libraries such as Pandas, NumPy, and Scikit-Learn, together with exposure to a deep learning framework such as TensorFlow or PyTorch. Understanding of the mathematical foundations of statistics, machine learning, and modern AI techniques. Strong understanding of model evaluation techniques, particularly for classification and clustering models. Familiarity with the use of AI coding agents such as Github Copilot, Claude Code, Cursor, Devin or others with the ability to critically examine AI code for fitness for use. Familiarity with LLMs, RAG, and AI agents Strong book-of-work management and organizational skills. Hands-on ability to manipulate data and tools to prototype and present solutions. Confident and self-motivated producer of original ideas and solutions, with sound judgment for when to escalate issues Strong written and verbal communicator with excellent presentation skills Ability to communicate complex technical concepts to colleagues and team members.