Data Intelligence Quality Manager

Southstate Bank•Va, NC

1d•Hybrid

About The Position

The Data Intelligence Quality Manager establishes and operationalizes a formal, enterprise-wide data quality program for SouthState Bank as part of the Data Intelligence Program (DIP), ensuring the Bank’s data is trusted, fit for use, and fit for purpose. This role stands up the data quality framework, standards, business rules, and monitoring needed to identify, measure, and remediate data quality issues across critical data elements, then manages and continuously improves those processes in partnership with Data Owners, Data Stewards, and Data Communities. The position exists to strengthen confidence in the Bank’s data as a strategic asset and to support sound decision-making, accurate reporting, and regulatory compliance.

Requirements

Bachelor’s degree in Data Management, Information Systems, Business Administration, Analytics, or a related field.
5+ years in data management, data governance, data quality, or a related data/analytics or process improvement role, preferably in banking or financial services.
Demonstrated experience establishing and executing data quality, data governance, or data management practices, including defining critical data elements, business rules, thresholds, and controls.
Experience with data profiling, data issue root-cause analysis, and remediation.
Demonstrated experience collaborating with cross-functional teams.
Project management experience, including developing and executing project plans and roadmaps.
Strong understanding of data quality dimensions (completeness, validity, accuracy, consistency, uniqueness, and timeliness), frameworks and best practices.
Working knowledge of data governance, data stewardship, metadata management, and data catalog tools (e.g., Atlan).
Proficiency with data profiling and analysis using SQL and/or data quality tooling, and with BI platforms (Power BI); familiarity with Snowflake is a plus.
Understanding of banking data, related regulatory and compliance considerations, and risk management practices.
Strong analytical, problem-solving, and root-cause analysis skills with high attention to detail.
Ability to build a program from the ground up—translating strategy into standards, processes, controls, and metrics.
Strong leadership, facilitation, and cross-functional influence without direct authority.
Excellent written and verbal communication skills, including executive-ready reporting.
Self-motivated, adaptable, and committed to continuous learning of data trends, tools, and best practices.

Nice To Haves

Banking experience and knowledge of applicable regulatory requirements preferred
Risk Management, Information Security, Information Technology, or Banking Operations experience is a plus.
Data management or data quality certification (e.g., DAMA CDMP), project management certification (PMP or CAPM), and/or relevant data platform certifications (e.g., Snowflake, Atlan, Power BI).
Familiarity with Snowflake is a plus.

Responsibilities

Establish the Bank’s formal, enterprise data quality program—designing, documenting, and implementing the data quality framework, standards, policies, procedures, and operating model that address the data quality dimensions (completeness, validity, accuracy, consistency, uniqueness, and timeliness) and embed data quality into the data or AI use case and onboarding lifecycle where applicable.
Partner with Data Owners, Data Stewards, and Data Communities to identify and document critical data elements (CDEs) and their associated business rules, data quality thresholds, and process flows; collect necessary metadata to support curation of CDEs within the data catalog.
Design, build, and operationalize automated and manual data quality controls, profiling, and monitoring against defined business rules; oversee routine identification of data errors and drive their remediation at the source to sustain ongoing quality.
Develop and maintain data quality metrics, scorecards, and/or Power BI reporting to measure data quality health and program effectiveness.
Manage the data issue lifecycle— lead root-cause analysis and implement remediation and preventative process improvements to reduce repeat issues.
Lead and support active data quality efforts and projects.
Lead, coach, and enable Data Owners, Data Stewards, and Data Communities on their data quality responsibilities; deliver data quality awareness and training as applicable; and promote a data-driven, quality-focused culture across the Bank.
Partner with IT/Data, Information Security, Risk Management, Compliance, Privacy, and Internal Audit as needed to align data quality processes with applicable standards and regulatory requirements and perform other duties as assigned.
Take ownership of all tasks and challenges that they encounter in the operation of their assigned position.