Data Engineering Architect

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. ## **Job Description** U.S. Bank is seeking a **Data Engineering Architect** to design and evolve modern data platforms that power enterprise data products, analytics, and AI-enabled solutions. Reporting to the Senior Data Engineering Architect, this role will help establish architecture standards, develop scalable platform patterns, and partner closely with engineering teams to deliver reliable, cloud-native data solutions. This position is ideal for a hands-on architect who enjoys solving complex technical challenges, building reusable frameworks, and enabling engineering teams to move faster through well-designed, scalable architecture. **What You'll Do** **Design Modern Data Platforms** - Define and implement architecture patterns supporting lakehouse, medallion, and domain-driven data platforms - Drive adoption of scalable, cloud-native data architecture and engineering best practices - Design reusable data products, models, and semantic layers that support analytics and business outcomes **Architect Data Pipelines & Solutions** - Design batch, real-time, streaming, CDC, and event-driven data solutions - Establish standards for scalability, performance, reliability, and resiliency - Partner with engineering teams to translate business and technical requirements into architecture designs **Enable Data & AI Innovation** - Support integration of AI, machine learning, and advanced analytics capabilities into data platforms - Contribute to modern platform capabilities that enable AI-ready data products and decision intelligence **Drive Engineering Excellence** - Create reusable frameworks, templates, architecture patterns, and best practices - Support DataOps capabilities including observability, data quality, lineage, and operational readiness - Promote secure, scalable, and maintainable solutions aligned to enterprise standards **Collaborate Across Teams** - Partner with product, engineering, architecture, and data science teams to support delivery of strategic data initiatives - Provide technical guidance and architectural expertise across multiple projects and teams **Basic Qualifications** - Bachelor's degree, or equivalent work experience - Eight or more years of relevant experience **Preferred Skills & Experience** **Data Platform & Engineering** - Experience designing modern data platforms using Databricks, Snowflake, or similar technologies - Strong background in distributed data processing using Python, PySpark, SQL, and related technologies - Experience designing batch, streaming, CDC, and event-driven data solutions - Knowledge of Kafka, Spark, and modern data integration patterns **Cloud & Architecture** - Experience with Azure and/or AWS cloud platforms - Strong understanding of scalability, performance, resiliency, and cost optimization - Experience designing enterprise-scale technical solutions and architecture patterns **Data Architecture & DataOps** - Experience with medallion architecture, data modeling, semantic layers, and KPI standardization - Familiarity with observability, data quality, lineage, SLAs, and operational support practices - Understanding of governance, security, and enterprise architecture principles **AI & Modern Engineering** - Exposure to ML lifecycle tools, feature stores, and AI-enabled data platforms - Familiarity with GenAI concepts, including LLM and RAG-based use cases - Experience with AI-assisted development tools such as GitHub Copilot is a plus…