Software Engineering Manager Legal Technology Data Platforms

Wells Fargo•Charlotte, NC

10d•Hybrid

About The Position

Wells Fargo is seeking a Software Engineering Manager to lead a globally distributed engineering team building, modernizing, and operating data platforms for Legal Technology. The platforms support legal data and operations, including legal hold, matter lifecycle management, and legal operations. The manager will combine engineering leadership, data expertise, and operational discipline to deliver trusted, secure, scalable, and well-governed solutions, while helping establish a data foundation for AI-enabled Legal capabilities. The role calls for a hands-on leader who stays connected to technology while coaching and developing engineers, solving complex problems, and partnering across Legal, Product, Architecture, Information Security, and Technology. The manager will translate evolving business needs into practical engineering solutions and will be accountable for delivery, engineering excellence, operational stability, talent development, and trusted organizational partnerships. The role offers a hybrid work environment with three days in the office.

Requirements

At least 5 years of software engineering experience, or equivalent demonstrated through work experience, training, military experience, or education.
At least 2 years of leadership experience.
At least 3 years of experience with data warehouses, data marts, data lakes, or similar data environments.

Nice To Haves

Experience applying technology, automation, AI, and data-driven solutions to legal workflows, including translating legal and business needs into scalable technology solutions.
Experience in Legal Technology or Legal Technology startups.
Experience leading software engineering, data engineering, data platform, or application development teams.
Strong knowledge of SQL, relational databases, ETL/data pipelines, APIs, integrations, and enterprise data environments.
Experience with modern engineering practices such as Git, CI/CD, automated testing, DevSecOps, Kubernetes, Helm, and secrets management.
Experience with data quality, governance, lineage, security, and privacy in complex or regulated environments.
Experience managing production applications, releases, incidents, vulnerabilities, and technology risk.
Ability to provide technical direction while coaching and developing engineering talent.
Experience leading or partnering with globally distributed and offshore engineering teams.
Strong communication, problem-solving, and stakeholder-management skills in a highly matrixed organization.
Experience with Legal or Compliance technology, including platforms such as Onit or Exterro.
Experience applying AI/ML or automation to enterprise workflows.

Responsibilities

Manage, coach, and develop a globally distributed team of engineers delivering Legal Technology data platforms, applications, pipelines, and integrations.
Lead delivery and modernization of data solutions supporting legal hold, matter lifecycle management, and legal operations.
Partner with architects and experienced engineers to align solutions with enterprise architecture, data strategy, application modernization, and technology standards.
Guide technical design and engineering quality across SQL, ETL and data pipelines, APIs, batch processing, secure file transfers, CI/CD, DevSecOps, and containerized environments.
Strengthen data quality, governance, lineage, access, retention, privacy, and readiness for AI-enabled capabilities.
Drive security and operational excellence through vulnerability remediation, technology currency, release management, production support, incident management, and root cause analysis.
Serve as an escalation point for complex engineering and production issues, removing roadblocks and improving platform reliability, scalability, and performance.
Partner with Product Managers and Product Owners to influence technology priorities, roadmaps, requirements, and delivery outcomes.
Foster a culture of accountability, collaboration, technical excellence, experimentation, and continuous improvement.
Identify opportunities to apply AI, machine learning, and automation to improve Legal Technology workflows and business outcomes.
Follow applicable risk programs, policies, and procedures; fulfill risk and compliance obligations; escalate and remediate issues; and make sound risk decisions.