Sr Data Warehouse Analyst

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
• 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.

Benefits

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from two to five weeks depending on salary grade and tenure)
• Up to 11 paid holiday opportunities
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

Pay Range

$105,400.00 - $124,000.00