Data Governance Operations Analyst

The Data Governance Operations Analyst acts as the operational coordination point for data governance and data quality services. In addition to governance, administration and reporting, the role is responsible for curating and enriching data quality incidents, translating technical alerts into business-relevant issues, performing preliminary impact assessments, and ensuring incidents are prioritised and communicated in a manner that supports effective decision-making by both business and technology stakeholders.

Responsibilities:

• Work closely with the Data Quality Lead and the Domain Governance Analysts and be the first-line coordinator for data quality incidents.
• Monitor Monte Carlo alerts and data quality notifications.
• Maintain governance operating procedures and runbooks, and contribute to governance maturity improvement initiatives.
• Review newly generated incidents and assess alert completeness and categorisation.
• Identify duplicate alerts and recurring issues.
• Create and maintain data quality incident records and escalate critical incidents in accordance with agreed procedures.
• Categorise incidents by domain, severity, data product, critical data element, root cause category, and impact type.
• Ensure incident information is complete before assignment and assign incidents to the correct domain or technology team.
• Identify opportunities to reduce recurring incidents.
• Track incident progress through to closure, monitor SLA compliance and follow up on overdue incidents.
• Maintain incident audit trails and evidence, and ensure incident status updates are current and accurate.
• Track unresolved ownership gaps and escalations.
• Maintain the enterprise data ownership and stewardship matrix and validate the completeness of ownership information.
• Support onboarding and offboarding of Data Owners and Data Stewards, and manage governance distribution lists, teams, channels and governance communities.
• Support stewardship engagement activities and coordinate periodic ownership reviews.
• Produce weekly data quality incident reports; track open incidents, closed incidents, repeat incidents, mean time to resolution, incident ageing, and top root causes.
• Support identification of systemic data quality issues and highlight trends requiring governance intervention.
• Maintain the lessons learned repository and identify operational inefficiencies within governance processes.
• Contribute to improvements in monitoring and triage processes.
• Recommend opportunities for automation and support the implementation of process improvements.
• Facilitate data access requests for roles requiring access to business systems and data.

Requirements:

• 3+ years of experience in data quality analysis, data quality principles, data management, or a related field.
• 2+ years of experience with SQL and database technologies, with the ability to query and analyse data sets.
• Prior experience of working with incidents, defects or operational support processes is essential.
• Proficiency in the use of Microsoft Excel, Power BI, Project, Word and PowerPoint.
• Prior knowledge of data governance programmes and/or data quality improvement programmes is essential.
• Ability to translate technical concepts into business language.
• Bachelor's degree in computer science, information systems, statistics, or a related field.
• Prior knowledge of the following tools, including Atlan, Monte Carlo, Snowflake, and Databricks, is desirable.
• Experience in tracking developments in Confluence/JIRA is highly beneficial.
• Prior experience of agile delivery is desirable.
• Excellent communication and documentation skills with the ability to present facts clearly and objectively.
• Excellent organisational and analytical skills with a high level of accuracy and attention to detail.
• Strong interpersonal skills with the ability to manage effective working relationships at all levels, both internally and externally.
• Proven ability to work effectively under pressure and commitment to producing high-quality output to tight deadlines.