Surveillance Data Engineering Manager

Wells Fargo is seeking a Surveillance Data Engineering Manager to lead the modernization of trade surveillance data platforms across asset classes including equities, fixed income, FX, and derivatives. This role blends strategic oversight with hands-on technical leadership to deliver scalable, regulator-ready solutions that support Market Conduct and Compliance functions. This role is responsible for the management of small-medium sized technology teams from US & India locations with the delivery/ execution accountability including people management. This is a player - coach role having technical/functional hands-on expertise and coach the team on technology and domain. Learn more about career areas and business divisions at https://www.wellsfargojobs.com.

In this role, you will:

• Manage, coach, and develop a team of individual contributor engineer roles with low to moderate complexity and less experienced managers who are responsible for building high quality capabilities with modern technology

• Ensure adherence to the Banking Platform Architecture, and meeting non-functional requirements with each release

• Engage with architects and experienced engineers to incorporate Wells Fargo Technology technical strategies, while understanding next generation domain architecture to enable application migration paths to target architecture, for example, cloud readiness, application modernization and data strategy

• Function as the technical representative for the product during cross-team collaborative efforts and planning

• Identify and recommend opportunities for driving resolution of technology roadblocks including code, build and deployment while also managing overall software development cycle and security standards

• Act as an escalation partner for scrum masters and the teams to make decisions and help remove impediments, obstacles, and friction while encouraging constant learning, experimentation, and continual improvement culture

• Build engineering skills side-by-side in the codebase, conduct peer reviews to evaluate quality and solution alignment to technical direction, and guide design, as needed

• Interpret, develop, and ensure security, stability, and scalability within functions of technology with low to moderate complexity, as well as identify, manage and mitigate technology and enterprise risk

• Collaborate and consult with the Product Managers/Product Owners to drive user satisfaction, influence technology requirements and priorities in the product roadmap, promote innovative and intelligent solutions, generate corporate value and articulate technical strategy while being a solid advocate of agile and DevOps practices

• Interact directly with third party vendors and technology service providers

• Manage allocation of people and financial resources for technology engineering including career development and performance management for engineers and managers on the team

• Hire, mentor and guide talent development of direct reports to build the skills required to effectively design and deliver innovative solutions for the supported product areas/products

Required Qualifications:

• 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• 2+ years of Leadership experience

Desired Qualifications:

• 4+ Years of experience and proven record of managing small and medium sized Data Engineering teams.

• 4+ years of leadership or management experience, in an IT environment

• Thought leadership, providing technical solutions working in tandem with the technical architecture team

•  Hands on experience in Python, Pyspark, ETL, Database modelling, Data Warehousing/Mining, Big data technologies (Hadoop), Optimization techniques & Reporting and Analytics

• Solid foundation in data modeling (conceptual/logical/physical) and database design

• Platform & DevOps

• Cloud-native engineering experience — serverless, managed Spark, event-driven architectures

• Strong experience implementing test automation for data pipelines (unit, contract, integration tests)

• Domain Expertise – Data Domains & exposure to Surveillance scenario

• Data Quality & Governance

• Knowledge of data governance platforms

• Understanding of data controls, validation rules, reconciliation checks, and compliance (SOX/PCI)

• Experience implementing lineage, observability, drift det