Lead Graph Data Engineer

Wells Fargo & Company•Iselin, NJ

1d•Onsite

About The Position

Wells Fargo is seeking a Lead Graph Data Engineer within the Fraud and Claims Technology organization. This role is central to building and expanding our enterprise graph database platform, which is used to uncover complex relationships that strengthen fraud detection and claims insights. You will lead the design and engineering of secure, compliant, and high performing data solutions. Your work will focus on graph data modeling, large scale data pipelines, and platform optimization across hybrid or cloud environments. With your background in database engineering and experience with graph technologies, you will help shape our analytics architecture, improve data governance, and turn connected data into meaningful intelligence that supports the bank’s fraud defense strategy.

Requirements

5+ years of Database Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
4+ years of experience with enterprise-scale data architecture and governance, including designing secure, compliant, and optimized data analytics platform across hybrid or cloud environments
2+ years of experience with Graph database design Neo4j or similar

Nice To Haves

Fraud Technology experience
Strong technical background across: PySpark, Spark, Hadoop, Hive, ETL/ELT tools (Informatica, Ansible etc.)
SQL & NoSQL databases (SQL, Oracle, PostgreSQL, MongoDB)

Responsibilities

Lead complex initiatives with broad impact and act as key participant in large scale software planning for the Technology area
Design, develop, and run tooling to discover problems in data and applications and report the issues to engineering and product leadership
Review and analyze complex software enhancement initiatives for business, operational or technical improvements that require in depth evaluation of multiple factors including intangibles or unprecedented factors
Make decisions in complex and multi-faceted data engineering situations requiring understanding of software package options and programming language and compliance requirements that influence and lead Technology to meet deliverables and drive organizational change
Strategically collaborate and consult with internal partners to resolve highly risky data engineering challenges