Credit Risk Data Engineer

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.

We actively uphold transparent and fair hiring practices that support individual opportunity, inclusive culture, and career mobility across all levels of our organisation.

We offer meaningful opportunities for growth, a culture of inclusion, and a strong commitment to transparency and integrity in everything we do.

About the Role  

The Credit Risk Data Strategy team within Credit Risk Management is seeking a Data Engineering Analyst with strong hands-on SQL and Python skills, experience building data pipelines and working with cloud-based data platforms, and a proven ability to work within complex, fragmented data environments. 

This role will support our multi-year modernization journey by helping transition Credit Risk data and processes from legacy platforms and SAS-based solutions to a modern cloud architecture built on Databricks, Snowflake, SQL, and Python. The individual will work closely with other Data Strategy team members, Technology, and business stakeholders to support data product development, source-system onboarding, migration activities, and modernized data processes. 

This role will help develop trusted, governed, and scalable data solutions for regulatory, forecasting, modeling, and reporting needs while improving automation, data quality, and operational efficiency. 

Role Responsibilities 

• Partner with other Data Strategy team members, business stakeholders, Enterprise Data Office, and Technology teams to support Credit Risk data modernization and data product initiatives.  

• Support the development of portfolio and cross-portfolio Credit Risk Data Products, ensuring data is trusted, governed, and aligned with business requirements. 

• Design, develop, test, and maintain scalable data solutions using SQL, Python, Databricks, and other modern data technologies. 

• Collaborate with Technology teams to onboard source-system data, document data requirements, and support future-state Credit Risk data architectures. 

• Develop and enhance data transformation, validation, reconciliation, and automation processes to improve efficiency, scalability, and data quality. 

• Support the modernization of Credit Risk data processes by migrating legacy SAS-based and SQL-based solutions to Python, SQL, and cloud-based platforms.  

• Develop reusable code, data pipelines, and automation solutions using established development standards and version-control practices. 

• Perform data analysis, profiling, and research across large and complex datasets to identify issues, trends, and improvement opportunities. 

• Support data governance activities, including data quality, lineage, controls, testing, and documentation. 

• Create and maintain technical documentation, process flows, playbooks, and training materials to support knowledge sharing and operational consistency. 

• Assist with troubleshooting, root-cause analysis, and remediation of data and processing issues. 

• Identify opportunities to leverage automation, AI, and machine learning to simplify processes, enhance data quality checks, and improve decision-making. 

Role Requirements 

• Bachelor’s degree in Information Systems, Computer Science, Mathematics, Statistics, Engineering, or a related field, or equivalent work experience. 

• 6+ years of experience in data engineering, data science, data analytics, or related technology roles. 

• Strong hands-on SQL and Python programming skills. 

• Experience working with large-scale datasets, developing data transformations, pipelines, validation routines, and reconciliation processes. 

• Experience with Databricks, Snowflake, Azure, AWS, or another cloud-based data platform. 

• Experience supporting data modernization, migration, cloud transformation, or data platform implementation initiatives. 

• Familiarity with data architecture, database design, data modeling, and data management concepts. 

• Strong analytical, problem-solving, and troubleshooting skills. 

• Ability to translate business and data requirements into maintainable technical solutions. 

• Strong communication and collaboration skills, with the ability to work effectively across business, data, and technology teams. 

Other Preferred Qualifications 

• Experience in Credit Risk, Regulatory Reporting, Banking, or Financial Services. 

• Experience with data quality, reconciliation, controls, and testing frameworks. 

• Experience developing reusable Python frameworks, automation solutions, and data pipelines. 

• Experience with Git-based version control, CI/CD pipelines, and deployment processes for data applications and data products. 

• Experience with Agile delivery practices and tools such as Jira or Azure DevOps. 

• Familiarity with Power BI or other data visualization and reporting tools. 

• Experience migrating SAS-based processes to SQL, Python, or cloud-based technologies. 

This role requires working from a U.S. Bank location three (3) or more days per week. 

Accessibility

We are committed to providing an inclusive and accessible recruitment experience. If you need adjustments at any stage of the application or hiring process, please contact your recruiter for guidance and support.

Total Rewards

U.S. Bank is committed to fair, equitable, and transparent compensation practices in line with local regulatory and legal requirements. Our total rewards approach is designed to attract, retain, and support top talent while ensuring equal pay for work of equal value.

We offer a market-competitive compensation package that includes:

• Clearly defined salary ranges aligned with industry benchmarks and internal equity standards.

• Performance-based incentives for eligible employees (as defined by relevant plan rules), awarded through transparent, objective criteria that recognize both individual and company performance.

• Inclusive equitable benefits that are accessible to all employees and focused around our 3 main pillars of financial wellbeing, health & wellness).

• Continuous development opportunities including training, education support, and career progression pathways based on inclusive and transparent criteria.

• Employee recognition programs that celebrate achievements and milestones for all.

We regularly review our compensation and benefits to ensure they remain competitive, inclusive, and responsive to employee needs and market trends. Further details of the compensation package will be provided upon application.

We encourage candidates to explore the full value of our offer, including monetary and non-monetary benefits, at Employee benefits and development | U.S. Bank | Elavon.

Closing Date

Posting may be closed earlier due to high volume of applicants.

We aim to provide timely updates throughout the process and encourage early applications to ensure consideration.