BMG Money

Director, Data Integrity

BMG Money

full-time

Posted on:

Origin:  • 🇺🇸 United States • Florida

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Job Level

Lead

Tech Stack

BigQueryCloudGoogle Cloud PlatformPythonSQLTableau

About the role

  • Design, implement, and own the enterprise-wide data integrity framework, including policies, standards, and procedures aligned with business objectives and regulatory requirements (e.g., FCRA, GLBA).
  • Define and own key quality indicators (KQIs) and metrics to measure the health of data across critical domains (e.g., Customer, Loan, Finance, Risk).
  • Develop and execute a comprehensive roadmap for data governance and data quality initiatives, prioritizing efforts based on business impact, risk mitigation, and strategic value.
  • Establish and support a federated data ownership model by working with domain-aligned Data Owners and Stewards to define, document, and maintain Critical Data Elements (CDEs).
  • Lead the operationalization of the governance lifecycle, including metadata management, data classification, lineage, and usage policies.
  • Facilitate Data Domain Councils and working sessions to drive accountability, resolve data issues, and ensure alignment across stakeholders.
  • Lead the data certification process to formally validate datasets for use in regulatory reporting, advanced analytics, and critical operations.
  • Design and deploy automated data quality (DQ) monitoring, alerting, and observability solutions using our cloud data platform (Google Cloud: BigQuery, Dataplex, Dataform) and visualization tools (Looker).
  • Collaborate with Data Engineering to embed automated DQ checks directly into data pipelines and CI/CD processes ("quality-by-design").
  • Develop and maintain data integrity dashboards for executive leadership and operational teams, providing transparent reporting on metrics, issue resolution status, and trend analysis.
  • Lead root cause analysis (RCA) for high-priority data issues, coordinating with data engineering, operations, and business teams to drive resolution.
  • Establish and manage a centralized data issue log with clear SLAs for remediation, distinguishing between tactical data fixes and strategic process or system improvements.
  • Escalate systemic risks related to data integrity to the Head of Data, the Data Council, and other relevant leadership.
  • Act as the primary subject matter expert and advocate for data governance and data quality across the organization.
  • Champion a culture of data accountability by developing training materials, promoting best practices, and demonstrating the value of high-quality, trusted data.
  • Serve as a key contributor to the Data Council, providing insights and support to drive data-driven decision-making.

Requirements

  • Bachelor's degree in Computer Science, Information Systems, Business Analytics, or a related quantitative field.
  • 8+ years of experience in a data-focused role, with at least 4+ years specifically dedicated to data governance, data quality, or data management.
  • Proven experience designing and implementing a data governance or data quality framework from the ground up in a complex business environment.
  • Expert-level proficiency in SQL for complex data profiling, analysis, and validation.
  • Hands-on experience with modern cloud data platforms (preferably GCP: BigQuery, Dataplex) and data governance or quality/observability tools (e.g., Monte Carlo, Great Expectations, Soda, Collibra DQ).
  • Deep understanding of data quality dimensions (e.g., Accuracy, Completeness, Timeliness, Validity) and common governance frameworks (e.g., DAMA-DMBOK).
  • Exceptional analytical and problem-solving skills with the ability to conduct rigorous root cause analysis.
  • Excellent communication and interpersonal skills, with a proven ability to influence and collaborate effectively with both technical and non-technical stakeholders.
  • Master's degree in a relevant field (preferred).
  • Experience in the financial services, lending, or fintech industry, with strong knowledge of regulatory requirements (e.g., FCRA, GLBA, CCPA) (preferred).
  • Knowledge of scripting languages like Python for data analysis and automation (preferred).
  • Experience with modern data stack technologies (e.g., dbt, Snowflake, Fivetran) and data visualization tools like Looker or Tableau (preferred).
  • Professional certification in data management or governance (e.g., Certified Data Management Professional - CDMP) (preferred).
  • Strong understanding of metadata management, data lineage, and data cataloging principles (preferred).