Data Quality Engineer

Bonus Type

Summary

BOK Financial is a top financial institution that offers a range of sophisticated financial products and services, focusing on personalized client relationships. With over a century of experience, we serve consumers, businesses, and wealth clients across the American Midwest and Southwest. We emphasize long-term relationships, community investment, and talent development, aligning with our brand platform, "We go above. So you can go beyond."

Job Description

The Senior Data Quality Engineer is responsible for supporting and executing enterprise-level data quality initiatives, including data profiling, measurement, process analysis, documentation, issue detection, root cause analysis, and remediation testing. This role partners closely with business and technical data stewards to identify data quality issues, recommend practical solutions, and contribute to the development and maintenance of business and data architecture artifacts.

The position plays a critical role in advancing a strong, sustainable data quality culture by ensuring that data quality practices are applied in a manner that supports business strategy, complies with regulatory expectations, and improves operational efficiency across the organization.

Team Culture

Our team thrives on collaboration, continuous learning, and innovation. We work closely together, leveraging cutting-edge technologies and sharing our expertise to solve complex problems efficiently. By encouraging creativity and adaptability, we experiment with new tools and methodologies, fostering a dynamic and tech-forward work environment. Additionally, we focus on creating a positive and supportive atmosphere, ensuring everyone feels valued and motivated to excel.

How You'll Spend Your Time

• You will profile and validate enterprise data to identify quality exceptions, trends, and root causes.
• You will analyze data quality issues for senior leaders and partners, providing clear recommendations for resolution.
• You will collaborate with Business and Technical Data Stewards to define quality rules, monitor metrics, and verify remediation results.
• You will develop and maintain data quality indicators, scorecards, and reports that strengthen transparency and decision‑making.
• You will contribute to improving enterprise data quality frameworks, standards, and best practices.
• You will ensure data quality considerations are embedded in system changes and data‑related initiatives.
• You will promote data quality awareness through documentation, training, and ongoing stakeholder engagement.
• You will build processes, KPIs, and metadata practices that support governance, MDM rules, regulatory requirements, and the adoption of BOKF tools and automation.

Education & Experience Requirements

This level of knowledge is normally acquired through completion of a Bachelor’s degree in MIS, Statistics, Computer Science, or a related field. Minimum 5–7 years of experience in a data-driven or data governance–focused role within the financial services sector is strongly preferred.

• Experience developing solutions on AWS or another cloud platform.
• Experience with cloud data warehousing (e.g., Snowflake) and SQL compilation/orchestration frameworks (e.g., dbt).
• Strong understanding of data quality practices and enterprise information management concepts
• Working knowledge of regulations such as CCPA, GDPR, HIPAA, SOX, and GLBA
• Strong SQL skills required
• Experience designing and executing data integrity and validation tests
• Experience with data modeling and process documentation tools
• Experience with Power BI or similar reporting tools preferred
• Strong written and verbal communication skills with the ability to translate complex data issues into clear insights
• Excellent analytical and problem-solving skills, including the ability to identify patterns, dependencies, and root causes
• Strong organizational skills with the ability to manage multiple priorities in a dynamic environment
• Ability to work independently while collaborating effectively across business and technical teams
• Demonstrated professionalism, curiosity, and commitment to data quality excellence