Sr. Business Intelligence Engineer - Digital Experiences & Capabilities
Listed on 2026-03-01
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IT/Tech
Data Analyst, Data Science Manager, Data Engineer, Data Security
Company Description
Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.
Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.
Job DescriptionJob Summary
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. In this role, you will partner with technology teams to design, build, and optimize the data foundation that powers Visa Marketing 360, define and maintain a flexible, scalable data model that adapts to evolving business and platform needs, and ensure that internal and external data sources are seamlessly integrated, cleansed, enriched, and ready for use in marketing campaigns.
Main Responsibilities
Data Engineering & Integration- 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.
- Ensure data model accommodates new data sources, changing business rules, and regional variations without disrupting existing operations.
- Collaborate with product and marketing teams to translate business requirements into robust data structures and relationships.
- Establish data governance standards to maintain consistency, accuracy, and compliance across the platform’s datasets.
- 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.
- Partner with marketing teams to translate data into actionable insights for targeting, personalization, and messaging strategies
- Contribute to A/B testing design and campaign measurement strategies
- Leverage AI to automate data preparation, segmentation, and campaign optimization workflows, reducing time-to-market and operational effort.
- Evaluate and deploy cutting-edge AI analytics tools to enhance decision-making speed, accuracy, and innovation in marketing execution.
- Work closely with the Sr. Product Manager to align data capabilities with platform strategy.
- Partner with Marketing Operations Lead to ensure data readiness for campaign execution.
- Provide training and guidance to marketing and operations teams on data tools, dashboards, and best practices.
- 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.
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
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