Data Engineering Architect

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. This role will help establish architecture standards, develop scalable platform patterns, and partner closely with engineering teams to deliver reliable, cloud-native data solutions.

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 (plus)