Sr. AI Transformations and Data Engineer – (Sr. Consultant level), PERC

Visa•Austin, TX

31d•$152,200 - $243,700•Hybrid

About The Position

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you’ll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you. Payments Ecosystem Risk & Controls (PERC), part of the Ecosystem Program (ERP), is responsible for identifying, managing, and mitigating risk across the global payments ecosystem. PERC partners with product, technology, data, architecture, operations, and regional risk teams to design and operate controls, monitoring programs, platforms, and analytics solutions that protect the integrity, security, and trust of Visa’s payment networks while enabling scalable and compliant business growth. Position Summary We are seeking an experienced Sr. AI Transformation and Data Engineer (Sr. Consultant level) to drive AI-enabled solutions, enterprise data products, platform modernization, and operational excellence across ERP/PERC platforms. This role operates at the intersection of data product management, AI, and business application support, requiring strong technical expertise, product thinking, and hands-on execution. The successful candidate will partner closely with business stakeholders, product managers, architects, engineers, and operations teams to design, develop, and enhance AI-enabled scalable products, deliver innovative solutions, and operational workflows that support risk intelligence, monitoring, investigations, and compliance programs across Visa's ecosystem. This individual contributor position requires the ability to translate complex business requirements into scalable technical and product solutions, contribute to AI transformation initiatives, support end-to-end delivery, and continuously improve platform capabilities through data, automation, and emerging technologies.

Requirements

8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience.
Bachelor's degree in computer science, Engineering, Data Science, Information Systems, Business, or related field.
8+ years of experience in product management, data products, platform management, analytics, or related disciplines.
Strong experience designing and managing enterprise-scale data products and integrations.
Hands-on experience supporting enterprise applications, issue triage, UAT, and release management.
Strong analytical, stakeholder management, and communication skills.
Ability to operate effectively in highly matrixed organizations.

Nice To Haves

9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD
10–12+ years of experience in product management, analytics, AI transformation, or data platforms.
Experience implementing or operationalizing Generative AI and AI-enabled solutions.
Experience in enterprise AI transformation or modernization initiatives.
Experience in payments, financial services, fintech, fraud, risk management, or compliance domains.
Experience managing external vendors, analytics providers, and discovery data sources.
Experience with Tableau, Power BI, or similar business intelligence platforms.
Knowledge of AI agents, GenAI, and workflow automation platforms, and intelligent assistants.
Experience with cloud data platforms and distributed architectures.
Understanding of enterprise architecture and large-scale system design.
Demonstrated ability to influence cross-functional stakeholders and drive execution.

Responsibilities

Drive AI transformation initiatives across PERC platforms by embedding Generative AI, Agentic AI, automation, copilots, and intelligent assistants into business and operational workflows.
Define and execute AI adoption roadmaps aligned with business objectives, governance requirements, and responsible AI principles.
Design AI-enabled product management workflows including discovery, requirements generation, backlog refinement, UX ideation, release readiness, and operational support.
Identify opportunities for summarization, classification, anomaly detection, investigation support, workflow automation, and decision intelligence.
Establish success metrics and value realization frameworks for AI adoption and productivity improvements.
Contribute to platform strategy, roadmap planning, and product execution aligned with ERP and PERC objectives.
Translate complex business, risk, operational, and data requirements into scalable platform capabilities.
Lead product lifecycle activities including discovery, roadmap planning, backlog management, release planning, UAT, and launch readiness.
Partner with architecture and engineering teams to evolve platform design, integrations, scalability, and resilience.
Develop business cases, data-driven recommendations, and prioritization proposals to support product and platform decisions.
Provide hands-on Business Application support, including intake, triage, prioritization, and resolution of user requests and incidents.
Manage and triage Business inquiries
Coordinate the root cause analysis on recurring issues and drive long-term corrective actions with technology teams.
Support release validation, post-release monitoring, onboarding, access management, and user enablement.
Track and communicate operational metrics, support trends, and platform performance.
Own enterprise data product strategy including ingestion, transformation, enrichment, access, and consumption requirements.
Design scalable cloud-based data and API contracts supporting high-volume, multi-source data ecosystems.
Integrate internal Visa and external vendor data sources into unified platform capabilities.
Define and enforce governance standards, lineage, metadata, access models, and quality controls.
Drive data standardization and harmonization across multiple discovery sources and systems.