Data Quality Lead

M&T Bank•Buffalo, NY

7d•Hybrid

About The Position

Leads and supports enterprise data quality efforts for the Customer 360 ecosystem, focusing on the accuracy, completeness, consistency, timeliness, and reliability of customer data used for analytics, marketing, customer communications, customer journeys, personalization, regulatory reporting, and operational processes. The position monitors, assesses, and improves data quality across the Enterprise Customer 360 platform, including Amperity, Snowflake, source applications, and downstream consumer systems. It partners with business stakeholders, technology and data engineering teams, data governance, marketing, analytics, and operational partners to identify, investigate, prioritize, and resolve data quality issues. The role involves investigative research, root cause analysis, testing, issue management, reporting, and continuous monitoring to keep customer data trusted and fit for purpose. It also supports platform enhancements, source data recertifications, monitoring initiatives, and the use of artificial intelligence and automation to improve data quality processes, controls, and operational efficiency. The position is hybrid, with four days onsite and one day remote, based at an M&T corporate location.

Requirements

Bachelor’s degree and at least 3 years of related experience, or a combined minimum of 7 years of higher education and/or work experience, including at least 3 years of related experience.
Experience with one or more database technologies.
Expertise in Structured Query Language (SQL), including advanced SQL.
Experience collecting and managing metadata.
Experience working in Data Governance and Data Quality programs at large, complex organizations.
Experience performing complex data analysis, testing, validation, and troubleshooting.
Strong SQL and data investigation skills.
Experience with large-scale enterprise data platforms and data warehouses.
Experience creating dashboards, scorecards, reporting, and data quality metrics.
Strong root cause analysis and problem-solving abilities.
Excellent written and verbal communication skills and ability to translate technical findings into business-friendly recommendations.
Ability to manage multiple priorities in a fast-paced environment.

Nice To Haves

Experience with the Amperity Customer 360 platform.
Experience supporting Customer 360, Master Data Management (MDM), Customer Data Platforms (CDP), or identity resolution solutions.
Experience with Snowflake.
Experience with Monte Carlo or comparable data observability platforms.
Financial services industry experience.
Experience with enterprise data governance and data stewardship programs.
Experience developing data quality frameworks, controls, and monitoring solutions.
Experience supporting marketing, customer communications, personalization, and customer journey initiatives.
Knowledge of customer identity resolution, householding, customer matching, and golden record methodologies.
Experience using AI and automation for data analysis, testing, monitoring, or issue management.
Intellectual curiosity and a passion for understanding and improving data.
Demonstrated ability to influence change across cross-functional business and technology teams.

Responsibilities

Support enterprise-wide data quality initiatives across the Customer 360 environment and serve as a subject matter expert for customer data domains and processes.
Develop understanding of customer identity resolution, golden record construction, customer hierarchies, and customer data integration.
Partner with data governance and business teams to define and maintain critical data elements, data quality rules, thresholds, and controls.
Monitor data quality metrics and identify trends, risks, and improvement opportunities.
Use Monte Carlo and other monitoring platforms to analyze alerts, anomalies, trends, and exceptions, determine root causes and business impact, and maintain data quality controls.
Develop dashboards, scorecards, and executive reporting on Customer 360 data quality health and performance across data quality pillars.
Lead data quality testing for system enhancements, platform upgrades, new source integrations, and process changes; develop test strategies, cases, validation procedures, and reconciliations.
Certify and recertify source system data; validate identity resolution outcomes, attribute mappings, transformation logic, and business rules.
Ensure data quality requirements are incorporated into project delivery and change management processes.
Conduct detailed data analysis, research, and troubleshooting; lead investigations involving multiple systems, business processes, and stakeholder groups.
Coordinate issue resolution across business, technology, analytics, and vendor teams; document findings, remediation plans, risks, and outcomes; track issues through resolution and validate corrective actions.
Support data quality activities for the Amperity Customer 360 platform and use Snowflake for analysis, reconciliation, monitoring, and warehouse investigations.
Collaborate with data engineering teams to validate pipelines, transformations, integrations, and downstream data consumption.
Support customer data availability and usability for analytics, campaign management, customer communications, and journey orchestration.
Identify improvements to data quality processes, controls, automation, and operational effectiveness; leverage AI and analytical tools for anomaly detection, issue identification, root cause analysis, documentation, testing, and reporting.
Recommend enhancements to monitoring frameworks, reporting, and data quality governance; contribute to enterprise data quality standards and best practices.
Partner with business and technology stakeholders to assess risks and prioritize improvements; communicate findings to technical and non-technical audiences, facilitate remediation discussions, and provide business recommendations.