The Data Steward & Analytics Specialist serves as a bridge between business operations and enterprise data management. The role is responsible for strengthening data quality, governance, reporting consistency, business metric standardization, and trusted analytics across the organization.
This position combines Data Governance, Data Quality, Business Intelligence, and analytics responsibilities. It plays a critical role in establishing trusted data foundations that enable analytics, artificial intelligence, regulatory compliance, operational excellence, and business growth.
Key Responsibilities
Data Governance and Stewardship:
• Define, document, and maintain business data definitions, rules, standards, ownership, and accountability.
• Support the implementation and operationalization of enterprise Data Governance practices.
• Maintain business glossaries, metadata, critical data elements, and data lineage documentation.
• Partner with business and technology stakeholders to establish ownership and stewardship of enterprise data.
• Participate in Data Governance forums, working groups, and issue-resolution processes.
Data Quality Management:
• Monitor Data Quality metrics, scorecards, controls, and trends.
• Perform data profiling and identify anomalies, gaps, and recurring quality issues.
• Develop, document, test, and maintain Data Quality rules and monitoring processes.
• Coordinate remediation activities with business and technology teams and track issues through closure.
• Perform root cause analysis and recommend sustainable corrective and preventive actions.
Analytics and Business Intelligence:
• Develop governed dashboards, scorecards, and reports using Power BI.
• Analyze business and operational data to identify trends, risks, and improvement opportunities.
• Support the definition, calculation, documentation, and standardization of enterprise KPIs and business metrics.
• Translate business questions into analytical requirements and actionable insights.
• Promote adoption of trusted data products, standardized metrics, and governed reporting.
Data Governance and Quality Platforms:
• Use Ataccama to support data profiling, Data Quality rule development, monitoring, business terms, and related governance activities.
• Collaborate with technical teams on Snowflake-based Data Quality and governance initiatives.
• Support metadata management, cataloging, lineage, issue management, and ongoing improvement of data controls.
• Contribute to the effective use and continuous improvement of enterprise Data Governance and Data Quality platforms.
Business Partnership and Data Literacy:
• Act as a liaison between business and technical teams.
• Help stakeholders understand data definitions, metric calculations, quality expectations, and reporting standards.
• Facilitate resolution of cross-functional data issues and promote accountability for data quality.
• Support data literacy and the consistent use of trusted information across business areas.