Credit Risk Data Engineer

Us Bank; Warszawa; Presencial; PLN 180.000 - 260.000; Jornada completa

Descripción de la vacante

U.S. Bank’s Elavon unit seeks a Data Engineering Analyst to join the Credit Risk Data Strategy team.

You will build data pipelines and migrate SAS-based solutions to a modern cloud architecture using Databricks, Snowflake, SQL, and Python to support data products, onboarding, migrations, and governance. This role requires 6+ years in data engineering, strong SQL and Python skills, and experience with large datasets and cloud platforms, collaborating with technology and business stakeholders to

Formación

• 6+ years in data engineering or related roles.
• Strong SQL and Python programming.
• Experience with large-scale datasets and data pipelines.
• Experience with Databricks, Snowflake, and cloud platforms.
• Knowledge of data governance and data quality.

Responsabilidades

• Partner with Data Strategy and Technology teams on modernization.
• Develop data products and onboard source-system data.
• Design, develop, test, and maintain scalable data solutions.
• Onboard source-system data and document data requirements.
• Improve automation, data quality, and efficiency.
• Create technical documentation and training materials.

Conocimientos

SQL

Python

Data pipelines

Data governance

Databricks

Snowflake

Cloud platforms

Educación

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

Herramientas

Databricks

Snowflake

Azure

AWS

Descripción del empleo

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 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 analytic