Senior Technology & Data Engineer

Job Description

About this role: Wells Fargo is seeking a Senior Software Engineer. We believe in the power of working together because great ideas can come from anyone. Through collaboration, any employee can have an impact and make a difference for the entire company. Explore opportunities with us for a career in a supportive environment where you can learn and grow. In this role, you will: Lead moderately complex initiatives and deliverables within technical domain environments Contribute to large scale planning of strategies Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals Lead projects and act as an escalation point, provide guidance and direction to less experienced staff Required Qualifications: 4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Quick frontend development experience Experience with frameworks such as Django, flask etc. Javascript and HTML foundational knowledge Experience in CI/CD pipeline development Familiarity with cloud platforms such as GCP, Azure etc. Job Expectations: Strong proficiency in Python Deep knowledge of Natural language Processing (NLP) : Text processing of structured and unstructured datasets. Hands-on experience with Gen AI (Open source models such as llama) : fine tuning, RAG method, Knowledge Graph Solid Machine Learning Background : Deep understanding of mathematics behind machine learning algorithms Version control systems such as git : primarily Github Experience with data pre-processing Drive data-driven initiatives leveraging advanced statistical techniques and ml algorithms