Senior Data Engineer with Data Analytics

Senior Data Engineer / Data Analytics

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 and enabling the communities we support to grow and succeed. 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 at every stage of your career.

Try new things, learn new skills and discover what you excel at—all from Day One.

Be a part of transformational change where integrity matters, success inspires, and great teams collaborate and innovate. As the fifth-largest bank in the United States, U.S. Bank is one of the country's most respected, innovative, ethical, and successful financial institutions. We're looking for people who want more than just a job—they want to make a measurable difference. U.S. Bank is seeking a Senior Data Analytics / Software Developer to help deliver modern, secure, scalable analytics and reporting solutions using Azure, SQL Server, Power BI, OLAP modeling, and enterprise database reporting practices in an Agile, AI-enabled technology environment.

This role is well-suited for a hands-on technologist who thrives in a small-team environment and is comfortable owning work across the full lifecycle—from requirements analysis and solution design through coding, testing, deployment, troubleshooting, and production support.

Be a part of transformational change where integrity matters, success inspires, and great teams collaborate and innovate. U.S. Bank is seeking a Senior Data Analytics / Software Developer who will contribute to the success of technology initiatives by analyzing, designing, developing, testing, deploying, and supporting enterprise data analytics and reporting solutions. This role will focus on building high-quality data products that enable trusted business insights, operational reporting, self-service analytics, and informed decision-making.

The ideal candidate combines strong software engineering discipline with deep experience in SQL Server, Azure data services, Power BI, OLAP/semantic modeling, data warehousing, and reporting methodologies. Because this role operates in a small-team environment, the candidate must be comfortable wearing multiple hats and taking practical ownership across all levels of the work: business analysis, technical analysis, database development, report development, testing, release coordination, troubleshooting, and production support.

The candidate will work in an Agile delivery model, partner closely with business and technology stakeholders, and apply AI-enabled tools and practices to improve productivity, quality, automation, and speed to insight.

Essential Responsibilities:

• Design, develop, test, deploy, operate, and maintain scalable data analytics, business intelligence, and reporting solutions using Azure, SQL Server, Power BI, OLAP, and related database reporting tools.
• Own end-to-end delivery responsibilities in a small team setting, including requirements clarification, data analysis, solution design, coding, unit testing, implementation, user support, issue resolution, and ongoing production stability.
• Build and optimize SQL Server databases, stored procedures, views, queries, data models, and reporting structures with attention to performance, reliability, maintainability, and security.
• Develop and maintain Power BI semantic models, dashboards, reports, measures, and datasets that provide accurate, actionable, and user-friendly insights for business and technology stakeholders.
• Design and support OLAP, dimensional, and semantic models that enable trend analysis, historical reporting, self-service analytics, KPI tracking, and executive reporting.
• Translate business requirements into technical solutions by collaborating with product owners, analysts, engineers, architects, scrum masters, and business partners, while also being able to perform detailed analysis independently when dedicated analyst capacity is limited.
• Apply data engineering and reporting best practices, including data quality validation, reconciliation, lineage awareness, metadata documentation, performance tuning, and controlled release processes.
• Contribute to cloud-based analytics solutions using Azure capabilities such as Azure SQL, Azure Data Factory, Azure Analysis Services, Microsoft Fabric, Synapse, Data Lake, or related services where applicable.
• Use AI-enabled development and analytics tools responsibly to accelerate requirements analysis, data profiling, code generation, test creation, documentation, anomaly detection, and continuous improvement.
• Follow Agile software development lifecycle practices, including backlog refinement, sprint planning, estimation, incremental delivery, demos, retrospectives, and proactive communication of risks or blockers.
• Take ownership of production-ready, testable, secure, and…