Job Details

This role requires candidates who are currently authorized to work in the U.S. without sponsorship, and C2C arrangements are not accepted. This role is remote.
Job Summary

The Collibra Data Quality Analyst is a strategic, technical role responsible for implementing and managing enterprise data quality and observability solutions to ensure data is accurate, consistent, reliable, and fit for business and regulatory use. This role designs data quality rules, monitoring processes, and remediation workflows, and acts as a bridge between technical teams and business stakeholders by translating business requirements into measurable data quality standards and actionable insights.

Key Responsibilities

• Partner with business and technical teams to identify data-related risks and establish appropriate data quality controls across key business processes.
• Define, monitor, and manage data quality standards related to accuracy, completeness, consistency, timeliness, and validity.
• Identify data quality issues, perform root-cause analysis, and drive remediation efforts across upstream and downstream systems.
• Support audit, regulatory, and reporting needs by ensuring data quality processes align with enterprise policies and governance standards.
• Develop strong knowledge of enterprise data policies and act as a subject-matter resource to educate stakeholders on data quality and governance expectations.
• Configure and maintain data quality and observability platforms and their integration with enterprise data ecosystems.
• Design and implement automated data quality rules, validation checks, and monitoring processes.
• Perform data profiling to identify anomalies, trends, and hidden data quality risks.
• Build and maintain data quality dashboards, scorecards, and alerts to provide real-time visibility into data health.
• Collaborate with data owners and stewards to define critical data elements (CDEs) and data quality thresholds.
• Facilitate issue management workflows, including documentation, prioritization, and resolution tracking.

• Strong experience with enterprise data quality, observability, or data governance platforms.
• Advanced SQL skills and experience working with large, complex datasets.
• Working knowledge of Python, Java, or similar languages for automation and integrations.
• Hands-on experience with modern data environments such as cloud data warehouses, data lakes, or distributed processing platforms.
• Solid understanding of data governance concepts including metadata, lineage, stewardship, and controls.
• Experience creating data quality reporting and exporting metrics to business intelligence or analytics tools.

• Strong analytical and problem-solving skills with the ability to detect data patterns, anomalies, and business impacts.
• Ability to translate technical data quality concepts into clear business language.
• Comfortable working cross-functionally with engineering, analytics, compliance, and business teams.
• Experience operating in Agile or project-based environments, including tracking and reporting initiatives.
• Highly organized, detail-oriented, and capable of managing multiple data quality initiatives simultaneously.