Software Engineering Senior Manager – Quantitative Data & Analytics

About this role:

Wells Fargo is seeking a Software Engineering Senior Manager Quantitative Data & Analytics to lead a team of engineering professionals supporting the modernization and transformation of the Wealth & Investment Management (WIM) analytics ecosystem. This leader willbe responsible forbuilding and developing a high-performing engineering organization focused on delivering scalable secure and reliable data solutions that power enterprise reporting analytics and business intelligence capabilities.

You will provide strategic direction for data engineering initiatives drive modernization of legacy platformsestablish governance and engineering best practices and partner closely with business and technology leaders to deliver high-value solutions. You will alsoleadthe build-out of an AI context layer (the semantic layer business ontology and context library thatgivesAI tools and analysts a trusted governed understanding of analyticsdata). You will oversee the large-scale data and analytics platforms that power it.

The ideal candidate willpossessstrong people leadership skills deep technicalexpertisein data engineering and the ability to execute complex initiatives while developing talent and fostering a culture of innovation accountability and continuous improvement.

In this role you will:

• Manage coach and develop a team orteamsof experienced data engineers and engineering managers in roles with moderate complexity and risk and support of enterprise data solutions.
• Ensure adherence to the Banking Platform Architecture and meeting non-functional requirements with each release
• Partner with engage and influence architects and experienced engineers to incorporate Wells Fargo Technology technical strategies while understanding next generation domain architecture and enable application migration paths to target architecture; forexamplecloud readiness application modernization data strategy
• Establish and execute strategic priorities that align data engineering capabilities with businessobjectivesand long-term technology roadmaps.
• Drive modernization efforts by transforming legacy reporting and data-processing environments into scalable governed and reusable data platforms.
• Oversee the design and implementation of enterprise-scale data pipelines data models data integration solutions and analytics platforms.
• Lead the design and build-out of an AI context layer (semantic layer business ontology context library and governed metadata). It should let AI assistants agents and self-service users work with WIM data accurately and safely and support change impact analysis.
• Operate and continuously improve large-scale data and analytics platforms with clear standards for reliability performance observability and cost.
• Evaluate and adopt new AI and data tools such as AI-assisted engineering automated metadata harvesting and ontology and knowledge graph platforms to accelerate delivery and scale the context layer.
• Ensure engineering standards controls governance practices and operational processes are consistently applied across the organization.
• Partner with technology leaders architects product owners and business stakeholders to prioritize work define requirements and deliver business outcomes.
• Lead resource planning workload management budget oversight and talent development initiatives to support organizational goals.

• Identifyopportunities to improve efficiency reduce technical debteliminateredundant data assets andoptimizedata processing capabilities.
• Drive adoption of modern data engineering practices including data orchestration automation monitoring and cloud-based technologies.
• Ensure compliance with enterprise risk security data management and regulatory requirements.
• Manage delivery of multiple initiatives while balancing competing priorities deadlines and stakeholder expectations.
• Foster a culture of collaboration innovation inclusion and continuous learning across the team.
• Interpretdevelopand ensure security stability and scalability within functions of technology with moderate complexity as well asidentifymanageand mitigate technology and enterprise risk
• Collaborate with partner with and influence 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
• Manage allocation of people and financial resources to ensure commitments are met and align with strategicobjectivesin technology engineering
• Hire build and guide a culture of talent development to have the skillsrequiredto effectively design and deliver innovative solutions for product areas and products to meet businessobjectivesand strategy as well as conduct performance management for engineers and managers

Required Qualifications:

• 7 years of Software Engineering experience or equivalentdemonstratedthrough one or a combination of the following: work experience training military experience education
• 7 years of Data Engineering experience or equivalentdemonstratedthrough one or a combination of the following: work experience training military experience or education.
• 3 years of management or leadership experience
• 3 years of experience operating large-scale enterprise data and analytics platforms (for example data warehouses data lakes orlakehouses ETL/ELT pipelines and BI environments)
• 2 years of experience using modern data and AI tools to build AI context layers (for example semantic layers business ontologies knowledge graphs or governed metadata) that ground AI and analytics solutions in enterprise data

Desired Qualifications:

• Experience building an enterprise AI context layer (semantic layer business ontology context library and governed versioned business definitions) that gives AI assistants agents and analysts a trusted consistent view of enterprise data.
• Experience designing business ontologies and knowledge graphs for financial services domains
• Experience with metadata management business glossaries data catalogs and lineage tools and using that metadata to power AI context and change impact analysis.
• Experience using emerging AI tools to accelerate data engineering and ontology development such as AI coding assistants automated metadata harvesting and LLM-assisted semantic mapping and grounding generative AI agents and natural-language analytics in enterprise data using techniques such as retrieval-augmented generation (RAG)GraphRAG vector search and Model Context Protocol (MCP) including testing outputs for accuracy.
• Experience running large-scale data and analytics platforms in production including observability SLAs incident and problem management capacity planning and cost optimization.
• Knowledge of responsible AI model risk and data privacy practices for AI solutions in financial services including controlling what data AI tools can access.
• Experience leading enterprise data modernization analytics transformation or large-scale reporting platform initiatives.
• Experience with cloud-based data platforms and modern data architectures.
• Experience with enterprise datalake datawarehouse ETL/ELT and data orchestration technologies.
• Experience supporting business intelligence and analytics platforms such as Power BI Tableau or similar technologies.
• Knowledge of financialservicesdata environments governance standards and regulatory requirements.
• Experience developing reusable and governed data assets that support self-service analytics.
• Experience with Agile delivery methodologies and product-based technology organizations.
• Experience implementing data governance data quality risk management and operational controls.
• Proven ability to build lead andretainhigh-performing teams.
• Strong executive presence and ability to communicate effectively with senior leadership.
• Bachelors degree or higher in Computer Science Information Systems Engineering Data Science or a related field
• Ability to influence collaborate and build relationships across multiple levels of the organization.
• Experience partnering with business and technology stakeholders to deliver strategic initiatives and technology solutions.
• Experience leading teams responsible for the design development and implementation of enterprise data solutions.
• Experience building and supporting large-scale data pipelines data integration frameworks and data platforms.
• Experience with data modeling database technologies data warehousing and enterprise reporting architectures.
• Experience managing multiple priorities complex projects and technology deliverables in a fast-paced environment.
• Strong leadership communication relationship management and organizational skills.

Job Expectations:

• This position offers a hybrid work schedule - ability to work in office
• This position is not eligible for Visa sponsorship
• Relocationassistanceis not available for this position

Posting End Date:

*Job posting may come down early due to volume of applicants.

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability status as a protected veteran or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit Market Financial Crimes Operational Regulatory Compliance) which includes effectively following and adhering to applicable Wells Fargo policies and procedures appropriately fulfilling risk and compliance obligations timely and effective escalation and remediation of issues and making sound risk decisions. There is emphasis on proactive monitoring governance risk identification and escalation as well as making sound risk decisions commensurate with the business units risk appetite and all risk and compliance program requirements.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates including women persons with disabilities aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

Applicants with Disabilities

To request a medical accommodation during the application or interview process visitDisability Inclusion at Wells Fargo.

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.

Wells Fargo Recruitment and Hiring Requirements:

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b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.