Senior Data Quality Specialist

The Senior Data Quality Specialist plays a critical role in ensuring the integrity, accuracy, and reliability of organizational data. Operating within the Data Governance Office, this role focuses on building and maintaining strong data quality frameworks, working with domain owners and stewards, and using modern tools and platforms to apply data standards and resolve quality issues at scale.

Main Accountabilities

• Develop and manage data quality rules, checks, and dashboards to ensure data is clean, complete, and reliable.
• Collaborate with Data Stewards, Domain Owners, and IT teams to identify, resolve, and prevent data quality issues.
• Monitor and report on data quality metrics (e.g., completeness, accuracy, consistency) using dashboards and reporting tools.
• Visualize and communicate data quality trends, issues, and improvements to stakeholders (experience with Power BI is a strong plus).
• Familiarity with data quality tools and automation approaches to support scalable rule enforcement.
• Contribute to the development and improvement of data standards, policies, and quality processes across the organization.

Requirements

Education, Experience and Technical Skills

• Bachelor’s degree in Computer Science, Data Science, Information Management, Business Analytics, or a related field (required); Master’s degree or certifications (e.g., CDMP, DAMA, data quality certifications) are a plus.
• 3+ years of experience in data quality, data governance, or data management roles, with increasing levels of responsibility.
• Hands-on experience designing and implementing data quality frameworks across multiple data domains.
• Strong experience with Databricks, Python, SQL, and PySpark for data profiling, transformation, and cleansing.
• Experience with data governance and metadata tools such as Collibra, Informatica, Alation, or Atlan is a plus (nice to have).

Competencies

• Strong analytical and root cause analysis skills, with a focus on solving data issues at scale.
• Excellent communication skills and the ability to translate technical findings into clear business impacts.
• Ability to assess the downstream effects of data quality changes on systems and processes.
• Proven ability to collaborate across departments and influence both technical and business stakeholders.
• Passion for data accuracy, operational excellence, and continuous improvement.