Data Quality Analyst

About the Role

The Data Quality Analyst will monitor, measure, and improve data quality across enterprise data domains including sales, finance, franchise operations, supply chain, loyalty, and customer data. This role combines technical data expertise with business problem-solving to build a scalable, trusted data foundation in a fast-paced, multi-brand restaurant organization. The ideal candidate will work closely with Data Engineering, Data Products, Business Intelligence, Data Governance, and business stakeholders to establish data quality standards, identify issues, implement controls, and drive continuous improvement.

Responsibilities

• Data Quality Management
  • Define, implement, and maintain enterprise data quality rules and controls.
  • Monitor data quality metrics including completeness, accuracy, consistency, timeliness, uniqueness, and validity.
  • Investigate and resolve data anomalies, discrepancies, and root causes.
  • Develop data quality scorecards and dashboards for business and technical stakeholders.
  • Establish data quality SLAs and KPIs across critical business datasets.
• Databricks Platform Responsibilities
  • Design and implement automated data quality checks within the Databricks environment.
  • Build and maintain data validation processes using Databricks SQL, PySpark, and Delta Lake.
  • Monitor data pipelines and data products for quality issues.
  • Partner with Data Engineers to embed quality controls throughout ingestion, transformation, and reporting processes.
  • Leverage Databricks workflows and monitoring capabilities to proactively identify data issues.
• Data Governance & Stewardship
  • Collaborate with data owners and business teams to define data standards and business rules.
  • Support master data management initiatives.
  • Document data definitions, lineage, quality rules, and issue resolution processes.
  • Participate in governance committees and data stewardship activities.
  • Ensure compliance with data governance policies and regulatory requirements.
• Analysis & Reporting
  • Conduct data profiling and quality assessments on new and existing datasets.
  • Perform root cause analysis and recommend corrective actions.
  • Create executive-level reporting on data quality trends and improvement initiatives.
  • Support audits and data validation efforts related to financial and operational reporting.
• Cross-Functional Collaboration
  • Work closely with Data Engineering, Data Products, Analytics & BI, Finance/Accounting, Operations, Supply Chain, and Marketing & Loyalty.
  • Translate business requirements into measurable data quality controls.
• Key Performance Indicators (KPIs)
  • Reduction in critical data quality incidents.
  • Improvement in enterprise data quality scores.
  • Percentage of automated data quality controls implemented.
  • Mean time to detect and resolve data issues.
  • Compliance with data governance standards.
  • Stakeholder satisfaction with data reliability and trust.

Requirements

• 3+ years of experience in Data Quality, Data Analytics, Data Governance, or related roles.
• Data Management certification (CDMP preferred).
• Strong SQL skills with experience querying large datasets.
• Experience working with cloud-based data platforms (Azure, AWS, or GCP).
• Knowledge of ETL/ELT processes and modern data architectures.
• Experience performing data profiling, validation, and reconciliation activities.
• Strong analytical and troubleshooting skills.
• Excellent communication and stakeholder management abilities.

Skills

• Required Technical Skills:
  • SQL
  • Delta Lake
  • Data Profiling
  • Data Validation
  • Root Cause Analysis
  • Data Governance
• Preferred Qualifications:
  • Experience in restaurant, retail, franchising, hospitality, or multi-location operations.
  • Experience with PySpark, Python, Databricks Workflows, Unity Catalog, Delta Live Tables, and Data Observability tools.
  • Familiarity with data governance frameworks and stewardship practices.
  • Knowledge of Master Data Management (MDM) concepts.
  • Experience implementing automated data quality frameworks.
• Preferred Technical Skills:
  • Databricks SQL
  • Databricks Lakehouse Platform
  • Python
  • PySpark
  • Azure Data Factory
  • Apache Spark
  • Unity Catalog
  • Delta Live Tables
  • Power BI
  • Git
  • CI/CD pipelines