Sr. Business Intelligence Engineer - Digital Experiences & Capabilities at Visa

Visa

San Francisco, CA, us·1h ago

SeniorFull-timeAIData

Salary Range

$132,600 - $179,400 /year

Estimated

This salary is estimated based on similar roles. The actual salary may vary.

About the Role

We are seeking a Hybrid Data Specialist with strong data engineering expertise and data analytics skills to play a critical role in building and optimizing the data foundation for Visa Marketing 360, Visa’s global marketing automation and personalization platform.

Key Responsibilities

→Partner with technology to prepare and maintain the data foundation for Visa Marketing 360, integrating multiple internal and external data sources and embed AI-driven data processing workflows to improve speed, accuracy, and scalability.
→Perform data cleansing, transformation, and enrichment to create high-quality datasets for marketing strategies.
→Integrate internal predictive models and Segmentation Engine into platform workflows.
→Develop processes to monitor and maintain data quality, proactively identifying and resolve issues.
→Partner with technology to build and maintain data pipelines that ensure reliable, real-time, and batch data availability for marketing campaigns
→Design, implement, and maintain a flexible, scalable data model that supports evolving marketing campaign requirements, advanced analytics, and AI-driven personalization strategies.
→Develop and maintain dashboards that incorporate AI-generated insights and predictive KPIs to guide marketing strategy.
→Analyze campaign and customer data to identify trends, patterns, and opportunities for optimization.
→Leverage AI to automate data preparation, segmentation, and campaign optimization workflows, reducing time-to-market and operational effort.
→Work closely with the Sr. Product Manager to align data capabilities with platform strategy.

Requirements

✓Engineering-first mindset: Builds scalable, efficient, and reliable data systems.
✓Data Model Architect: Designs structures that adapt to evolving business needs
✓Analytics-Driven: Uses data to uncover insights and improve decision-making
✓AI Innovator: Seeks out opportunities to embed AI into every stage of the data lifecycle for better speed, accuracy, and impact.

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