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Lead Data Product Management Consultant

Actively Reviewing the Applications

Wells Fargo

India, Karnataka Full-Time On-site

Posted 1 hour ago • Apply by June 11, 2026

Job Description

About This Role

Wells Fargo is seeking a Lead Data Product Management Consultant.

In This Role, You Will

Lead complex data product initiatives, including those that are cross-functional with broad impact, and act as key participant in large-scale planning driving data enablement and capabilities across platforms and utilities
Review and analyze complex multi-faceted, larger scale or longer-term data product initiatives that require in-depth evaluation of multiple factors, including intangibles or unprecedented factors to drive data enablement strategies and roadmaps, while adhering to set data governance and standards
Make decisions in complex and multi-faceted situations requiring solid understanding of data, analytics, and integration needs of line of business partners to inform prioritization, roadmap, and architecture design, that influence and lead broader work team to meet deliverables and drive new initiatives
Strategically collaborate and consult with peers, colleagues, and mid-level to senior managers to ensure data product solutions are built for optimal performance and design analytics applications across multiple platforms, resolve data product issues, and achieve goals; may lead projects, teams or serve as a peer mentor
Provide strategic input on new use case intake, prioritization, product roadmap definition, and other critical business processes
Manage complex datasets continuously focusing on the consumers of the data and their business needs, while adhering to set data governance
Create and maintain data product roadmaps throughout the data product life cycle with detailed specifications, requirements, and flows for data capabilities
Design and maintain innovative data products, enabling data availability for data intelligence, analytics, and reporting
Serve as a strategic liaison between data management, product teams, data engineering, and architecture teams throughout the data product life cycle

Required Qualifications

5+ years of data product or data management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications

Lead end-to-end analytics projects, from requirement gathering to solution delivery.
Design and implement scalable data models, pipelines, and governance frameworks.
Partner with business stakeholders to identify opportunities for advanced analytics and predictive modeling.
Provide thought leadership on data strategy, architecture, and emerging technologies.
Mentor and guide junior consultants and analysts, ensuring adherence to best practices.
Drive innovation by exploring and applying Gen AI, machine learning, reusability and automation techniques.
Collaborate with cross-functional teams (Business, Technology, Operations) to align analytics solutions with organizational goals.
Ensure compliance with data security, privacy, and regulatory standards.
Fluent in agile ways of working and agile project management practices, proficient in creating efficient user stories, and other agile project artifacts.

Job Expectations

Proven expertise in data analysis, data management, and data engineering.
Strong proficiency in SQL, Python/R, and advanced analytics tools.
Experience with cloud platforms (Azure, AWS, or GCP) and big data technologies.
Ability to design and optimize data pipelines and workflows.
Excellent problem-solving and critical-thinking skills.
Strong communication and stakeholder management capabilities.
Proficiency in Python programming with hands-on experience in developing and debugging code.
Exposure to data science (modelling, ML, statistical forecast).
SQL: Ability to write, read, and optimize queries for data extraction, transformation, and analysis.
Experience with Google Data Cloud stack (Dataplex, big query, etc.).
Experience with metadata management and data governance practices.
Proficiency in data profiling and root cause analysis for data quality issues.
Hands-on experience with machine learning, AI, and Gen AI applications.
Familiarity with data visualization tools (Power BI, Tableau).
Knowledge of data governance frameworks and best practices.
Experience in leading large-scale analytics transformations.
Ability to influence strategic decisions through data-driven insights.