Wells FargoSenior Lead Data Management Analyst
Wells Fargo is hiring a Senior Lead Data Management Analyst in Bengaluru, India. Level rates it ; you can apply on Wells Fargo.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include RAG, data management and semantic modeling.
- Level classifies it as a senior role.
- Level lists 1,500+ other open roles at Wells Fargo.
- The role was posted in the last few days.
AI in this role
Translate priority AI and data use cases into governed data, semantic capabilities, ontologies, and grounding context for reliable AI solutions.
About this role:
Wells Fargo Wealth & Investment Management (WIM) Data Management is seeking a Senior Lead Data Management Analyst to serve functionally as the Strategic Data & Intelligence Enablement Leader. Reporting to the WIM Data & AI Strategic Enablement Leader, this senior individual contributor will translate priority business, data, and AI use cases into governed data and semantic capabilities.
The role will lead business-to-data translation, source decisioning, data mapping, semantic modeling, and data-product adoption. For AI-native initiatives, it will define the ontologies, metadata, knowledge representations, grounding context, provenance, and controls needed for reliable AI solutions. The role will partner with Data Product Designers, architects, engineers, governance teams, and business stakeholders while remaining focused on strategy, requirements, design direction, and adoption rather than product engineering.
In this role, you will:
Act as an advisor to leadership to develop or influence objectives, plans, specifications, resources, and long-term goals for highly complex business and technical needs
Design and conduct highly complex analysis to identify and remediate data quality or integrity issues and to identify and remediate process or control gaps
Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking
Evaluate data quality metrics and data quality audits to benchmark the state of data quality
Provide vision, direction, and expertise to senior leadership on implementing innovative and significant business solutions
Recommend remediation of process or control gaps that align to management strategy
Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership
Represent client in cross-functional groups to develop companywide data governance strategies
Partner with groups companywide to coordinate and drive collaboration on solution design and remediation execution
Translate business and AI use cases into scalable data product solutions.
Analyze and evaluate data sources, mappings, transformations, and business rules.
Define data, semantic, grounding, and traceability requirements for AI applications.
Assess data quality, lineage, metadata, privacy, and governance readiness.
Identify and mitigate data, AI, and semantic risks.
Establish end-to-end data lineage and control frameworks.
Partner with business, technology, risk, compliance, privacy, and architecture teams to deliver governed data solutions.
Required Qualifications:
7+ years of Data Management, Business Analysis, Analytics, or Project Management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of hands-on experience translating business needs into data requirements, source decisions, mappings, analytical findings, or governed data solutions
7+year of strong background in Data Management, Data Governance, Business Analysis, Data Product Management, and AI Enablement.
Hands-on experience with SQL, data profiling, metadata management, data lineage, and data quality frameworks.
Experience in AI data readiness, semantic models, APIs, governance, and risk controls.
Excellent stakeholder management and problem-solving skills.
Desired Qualification
Financial services experience, preferably in Wealth Management, Investment Management, Brokerage, Fiduciary Services, or Regulatory Reporting.
Strong background in Data Strategy, Data Governance, Data Architecture, Metadata, and Data Product Management.
Hands-on expertise with data analysis, SQL, data profiling, lineage, and quality management.
Experience with Semantic Technologies and Knowledge Graphs (RDF, OWL, SPARQL, SHACL, JSON-LD, FIBO, Protégé).
Familiarity with Generative AI, RAG (Retrieval-Augmented Generation), Agentic AI, and AI governance frameworks.
Proven ability to lead complex enterprise initiatives, influence senior stakeholders, and mentor teams.
Posting End Date:
26 Oct 2026*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 unit’s 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, visit Disability 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:
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.
How we rate this
Senior Lead Data Management Analyst at Wells Fargo rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Tell me about a project where data management was part of your work. What did you do?
- Tell me about a project where semantic modeling was part of your work. What did you do?
- Tell me about a project where data governance was part of your work. What did you do?
- Tell me about a project where ontologies was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, Data Management, Semantic Modeling, Data Governance, and Ontologies. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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