Data Product Manager

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions, enabling the communities we support to grow and succeed in the right ways, all more confidently and more often—that’s what we call the courage to thrive. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential.

A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive. Try new things, learn new skills and discover what you excel at—all from Day One.

As a wholly owned subsidiary of U.S. Bank, Elavon is committed to building the platforms and ecosystems that help over 1.5 million customers around the world to achieve their financial goals—no matter what they need. From transaction processing to customer service, to driving innovation and launching new products, we’re building a range of tailored payment solutions powered by the latest technology.

As part of our team, you can explore what motivates and energizes your career goals: partnering with our customers, our communities, and each other.

We are looking for a Product Manager with experience leading the design and implementation of Data Products on the Microsoft Azure platform. This role requires hands on experience with cloud native solutions to meet the complex Data and Insights requirements of our customers, while increasingly leveraging modern AI native, Copilot driven, and agentic product development practices.

The Product Manager will play a critical role in shaping and delivering scalable, intelligent data platforms that not only organize and integrate disparate data sources, but also enable AI powered, insight driven, and increasingly autonomous data experiences.

• Gather and analyze business and technical requirements to develop impactful Data Solutions, leveraging both traditional discovery techniques and AI assisted insights.
• Demonstrate expertise through a consultative and collaborative approach to engineering, working closely with data engineering, data science, and platform teams.
• Apply strong problem solving skills grounded in a deep understanding of data architectures, pipelines, data warehouses, serving layers, and modern analytics patterns.
• Document end to end data flows from source to target at a functional level, ensuring clarity, traceability, and alignment with business outcomes.
• Investigate and perform deeper analysis to produce high impact data solutions that achieve targeted and measurable outcomes.
• Perform quantitative analysis to identify, diagnose, and resolve data quality, performance, and reliability issues.
• Work closely with customers to understand their questions and needs, then navigate data rich environments to uncover insights and complete their information puzzle.
• Effectively communicate—both orally and in writing—with peers across Data Products, Enterprise Architecture, Technology, and Client Success teams.
• Leverage Microsoft Copilot and AI assisted tooling across the product lifecycle, including requirements discovery, backlog refinement, technical documentation, data analysis, and stakeholder communication.
• Use AI driven insights to accelerate problem discovery, hypothesis validation, prioritization, and decision making.
• Partner with engineering and data science teams to embed AI assistance directly into data products, dashboards, and workflows, improving end user decision quality and efficiency.
• Contribute to the design of agentic data systems, where autonomous or semi autonomous agents assist with data quality monitoring, anomaly detection, root cause analysis, pipeline orchestration, and operational observability.
• Support the evolution from traditional dashboards to AI powered, conversational, and goal oriented data experiences that adapt to user context and intent.
• Help define scalable product patterns where intelligent agents proactively surface insights, recommend actions, and continuously learn from usage signals.
• Apply modern, AI enabled product discovery techniques to synthesize customer feedback, operational telemetry, and…