Solutions Architect - Data Solutions (MS SQL Server & Oracle, AWS)

U.S. Bank • Atlanta, GA

1d • Onsite

About The Position

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, enabling the communities we support to grow and succeed in the right ways, all more confidently and more often—that’s what we call the courage to thrive. 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. Try new things, learn new skills and discover what you excel at—all from Day One. As a wholly owned subsidiary of U.S. Bank, Elavon is committed to building the platforms and ecosystems that help over 1.5 million customers around the world to achieve their financial goals—no matter what they need. From transaction processing to customer service, to driving innovation and launching new products, we’re building a range of tailored payment solutions powered by the latest technology. As part of our team, you can explore what motivates and energizes your career goals: partnering with our customers, our communities, and each other. Job Description U.S. Bank is seeking a detail-oriented Data Architect with relational database and logical/physical database modeling experience to contribute toward the success of our technology initiatives. Data Architects design and oversee the implementation of data solution architectures within organizations. They are responsible for translating business requirements into robust data models, ensuring compliance with relevant regulations, and collaborating with cross-functional teams to develop scalable and secure data systems. Why Data Solution Architecture Matters: Data solution architecture is essential for organizations aiming to leverage data effectively for decision-making, analytics, and AI. It ensures that data is not only stored but also optimized for accessibility, security, and future scalability.

Requirements

• Bachelor's degree, or equivalent work experience
• Five to eight years of related experience

Nice To Haves

• Expertise in enterprise data architecture and database design, including conceptual, logical, and physical data modeling.
• Strong experience with data modeling tools (e.g., ERwin) and hands‑on design of relational databases such as Microsoft SQL Server and Oracle.
• Proficiency in SQL and Python for data analysis, transformation, and architecture support.
• Deep understanding of modern data platforms and architectures, including cloud data warehouses (Azure Synapse, Snowflake, BigQuery), data lakes, lakehouse architectures, and real‑time data pipelines.
• Strong knowledge of data governance, security, privacy, metadata management, and data quality, including experience working within regulated or compliance‑driven environments (e.g., GDPR, HIPAA, SOC2).
• Experience designing scalable, secure, and high‑performance data solutions that support enterprise analytics and reporting needs.
• Ability to translate business requirements into technical data architectures, collaborating closely with engineering, analytics, and business stakeholders.
• Excellent communication skills, with the ability to clearly explain complex data and architectural concepts to both technical and non‑technical audiences.
• Knowledge/experience designing AI‑ready data architectures that enable analytics, machine learning, and AI‑driven applications.
• Understanding of how data is structured and prepared for machine learning workflows, including feature‑friendly data models and data reproducibility concepts.
• Familiarity with real‑time and streaming data architectures that support AI/ML use cases such as fraud detection, alerts, and personalization.
• Awareness of the machine learning lifecycle and MLOps concepts, including data pipelines for model training, deployment, monitoring, and retraining (architect‑level understanding).
• Knowledge of how AI and generative AI solutions consume enterprise data, including secure data access, governance, and retrieval‑based analytics patterns.

Responsibilities

• Design and implement data solution architectures aligned with business needs.
• Translate business requirements into logical and physical data models.
• Ensure data systems comply with industry regulations and organizational policies.
• Collaborate with engineering, analytics, and business teams to deliver scalable and secure data solutions.
• Optimize data storage, accessibility, and security for current and future needs.
• Design and implement data pipelines to support machine learning and AI initiatives.
• Collaborate with data scientists to ensure data quality, consistency, and availability for model training and deployment.
• Develop and maintain data architectures that enable advanced analytics, predictive modeling, and AI-driven applications.
• Integrate structured and unstructured data sources to support AI/ML use cases.
• Ensure data architectures are optimized for large-scale data processing and real-time analytics.
• Support the deployment and monitoring of machine learning models in production environments.
• Evaluate and recommend new technologies and frameworks for AI and ML data management.
• Establish best practices for data versioning, lineage, and reproducibility in AI/ML workflows.

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
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level