Credit Risk Data Lead

Us Bank; Warszawa; Hybrid; PLN 180,000 - 280,000; Full time

Job summary

U.S. Bank is seeking a Data Lead for Credit Risk Data Strategy to drive modernization from SAS to SQL/Python on Databricks. You will coordinate with Technology, Enterprise Data Office, and business stakeholders to deliver scalable data solutions and governance.

The role focuses on production data products, data quality, and regulatory data processes, with a path to leadership in data preparation and maintenance.

Qualifications

• Bachelor’s degree or equivalent in a related field.
• 8+ years in data, analytics, reporting, or tech roles.
• Experience leading projects or small teams.
• Production‑ready code with testing and Git versioning.
• Experience with Databricks, Snowflake, Azure or AWS.

Responsibilities

• Partner with stakeholders to support Credit Risk data product initiatives.
• Develop and maintain scalable data solutions using SQL, Python, Databricks.
• Onboard source-system data and define data requirements.
• Improve data transformation, validation, and automation processes.
• Create reusable code frameworks and migration patterns.
• Modernize SAS-based solutions to SQL/Python and Databricks.
• Contribute to data governance, quality, and documentation.
• Develop technical playbooks and training materials.
• Explore automation and ML to improve data quality.

Skills

SQL

Python

Databricks

Data architecture

Leadership

Cloud platforms

Education

Bachelor’s degree in Information Systems, Computer Science, Mathematics, Statistics, Engineering, or related field

Tools

Git

CI/CD

Job description

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.

Job Description

About the CRA Team

We are a highly dynamic and talented team which delivers on our mission through four pillars: Customer, Process, Talent, and Data.

• Vision | We create the future of credit risk management through data, analytics, and risk process innovation for our customers.

• Mission | We deliver data-driven information solutions to protect our stakeholders and inform the most significant financial decisions in the bank.

• Values | In addition to U.S. Bank core values, we prioritize collaboration, integrity, simplicity, and continuous learning.

About the Role

The Credit Risk Data Strategy team within Credit Risk Management is seeking a Data Lead with strong SQL and Python skills, a solid understanding of data architecture and database design, and hands‑on experience working with complex, fragmented data environments.

This role will play a key part in our multi-year modernization journey, helping transition Credit Risk data and processes from legacy platforms and SAS-based solutions to a modern cloud architecture built on Databricks, SQL, and Python. Working closely with Technology, Enterprise Data Office, and business stakeholders, the individual will provide technical leadership and coordination for modernization initiatives, support regulatory, forecasting, modeling, and reporting data processes, and help establish a trusted, governed, and scalable future-state data framework.

The initial focus of the role will be on supporting Credit Risk data modernization initiatives. As the modernized environment matures, responsibilities will progressively expand to include ownership, maintenance, and ongoing enhancement of production data products and processes.

Role Responsibilities

• Partner with business stakeholders, Enterprise Data Office and Technology to support Credit Risk data product initiatives for reporting, forecasting, modeling, and regulatory needs.

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

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

• Collaborate with Technology teams to onboard source-system data, define 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.

• Create reusable code frameworks, migration patterns, and best practices to accelerate modernization efforts across the organization.

• Modernize Credit Risk data processes by migrating legacy SAS-based solutions to SQL/Python and Databricks.

• Contribute to data governance activities including data quality, lineage, controls, and documentation.

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

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

• Support the transition of production data processes from legacy platforms to modern cloud-based solutions, ensuring operational stability, data quality, and regulatory compliance throughout the migration.

• Develop deep knowledge of Credit Risk data products and production processes, progressively assuming leadership responsibility for production data preparation and maintenance activities while helping establish a sustainable operating framework.

Role Requirements

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

• 8+ years of experience in data, analytics, reporting, or technology-related roles.

• Experience leading projects, initiatives, or small teams, including coordinating work across stakeholders.

• Strong SQL and Python programming skills, including experience writing production‑ready code with testing, documentation, Git‑based version control, and operational support considerations.

• Experience with Databricks, Snowflake, Azure, AWS or other cloud‑based data platforms.

• Strong understanding of data architecture, database design, data modeling and data management concepts.

• Experience working with large‑scale datasets and complex data transformation.

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

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

• Ability to translate business requirements into scalable technical solutions and manage stakeholder expectations.

• Ability to operate effectively in both project‑based modernization initiatives and ongoing production support environments.

• Experience in Credit Risk, Regulatory Reporting, Banking, or Financial Services, for example supporting CCAR, CECL, forecasting, regulatory reporting, or modeling processes.

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

• Experience working within data production, operational support, reconciliation, or model production data processes.

• Experience leading or coordinating offshore and distributed delivery teams.

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

• Experience working with CI/CD pipelines and deployment processes for data applications and data products.

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.

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.