Sr Data Warehouse Analyst

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.

Key Responsibilities Design, develop, and maintain enterprise-scale Data Warehouse, Data Lake, and Lakehouse solutions supporting operational reporting, analytics, and AI/ML initiatives. Build and enhance scalable data models, database architectures, and data storage frameworks to support business, analytical, and operational requirements. Develop, optimize, and support batch, streaming, and near real-time ETL/ELT pipelines using SQL, Python, cloud-native services, and modern data integration technologies. Integrate, transform, and manage structured, semi-structured, and unstructured data from multiple internal and external data sources while ensuring data quality and reliability. Implement and support enterprise data integration solutions utilizing Informatica, IBM DataStage, or similar ETL/data integration platforms . Partner with business stakeholders, analysts, architects, and application teams to gather requirements and deliver scalable, high-performing data solutions. Enable business intelligence, advanced analytics, and AI/ML use cases by preparing, optimizing, and governing datasets for enterprise consumption. Monitor, troubleshoot, and tune data platforms and pipelines to ensure high availability, performance, scalability, automation, and operational excellence . Implement and support cloud-based data solutions leveraging AWS, Microsoft Azure, or Google Cloud Platform (GCP) services. Apply enterprise standards for data governance, security, privacy, compliance, and metadata management to protect organizational data assets. Basic Qualifications -Bachelor's degree or equivalent work experience -At least 5 years experience with tools, facilities and techniques for managing and administering data. Preferred Skills/Experience Hands on experience in Data Engineering, Data Warehousing, ETL/ELT Development, Data Integration, or Data Management roles. Advanced proficiency in SQL with hands-on experience in data modeling, database design, query optimization, and performance tuning. Strong programming experience with Python for data processing, automation, orchestration, and engineering solutions. Experience designing and supporting modern Data Warehouse, Data Lake, Lakehouse, and distributed data architectures . Hands-on experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (GCP) . Experience developing scalable ETL/ELT pipelines using SQL, Python, cloud-native services, and enterprise integration tools. Knowledge of modern big data and orchestration technologies such as Apache Spark, Databricks, Airflow, or related platforms . Experience with Git, GitHub, Azure DevOps, CI/CD pipelines, and DevOps best practices for data engineering. Understanding of data governance, data quality, security, privacy, compliance, and metadata management principles. Familiarity with AI-assisted development tools such as GitHub Copilot, ChatGPT, Claude, or similar productivity solutions, along with strong analytical, problem-solving, communication, and stakeholder management skills. Location expectations   This role requires working from a U.S. Bank location three (3) or more days per week. If there’s anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to our  disability accommodations for applicants .

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