Data Quality Analyst

Must Have Technical/Functional Skills
• 3+ years in business analyst, data analyst, or similar roles involving direct stakeholder-facing requirements gathering.
• 1+ year exposure to data quality, data governance, or data management initiatives preferred.
• Ability to translate ambiguous business language into precise, testable requirements; including


relationship/correlation requirements across entities
• Working SQL skills sufficient to explore data independently, validate assumptions, and communicate credibly


with engineers (advanced development skills not required).
• Strong facilitation and communication skills, comfortable working live with both technical teams and non-technical


business stakeholders at multiple levels.
• Organizational and follow-through skills for managing a backlog, tracking commitments across many stakeholders,


and keeping a distributed process on track.
• Experience producing clear documentation and stakeholder-facing reporting.


Roles & Responsibilities


Requirements & Rule Backlog
• Partner with business stakeholders to define data quality requirements organized by business function and


subject area, framing quality in terms of the business capabilities it enables.
• Within each subject area, identify and document the critical data elements, quality expectations, thresholds,


severity, and the steward/owner responsible for triage.
• Define cross-entity correlation requirements as first-class quality rules alongside field-level checks.
• Work with stakeholders to define derived, subject-area-level quality scores tied to business


readiness (e.g., readiness of quote and exposure data to support new product development or provisional quoting),


so quality is measured against outcomes.
• Own and prioritize the data quality rule backlog by subject area, balancing business impact, regulatory importance,


and engineering effort in partnership with the Data Quality Engineer.
• Validate implemented rules with business stakeholders before deployment, confirming the rule measures what the


business intended.
• Maintain traceability between business requirements, implemented rules, and the subject areas and systems


they cover


Steward Enablement & Program Oversight
• Onboard and train Business Data Stewards and data owners on the decentralized alert and triage model,


including how to interpret, work, and resolve alerts in DQLabs.
• Develop and maintain steward-facing materials: triage guides, alert response expectations, escalation paths, and FAQ


documentation.
• Monitor the health of the steward network: track alert response and resolution rates, identify stale or unworked alerts,


and follow up with stewards and their leadership when triage lags.
• Manage the escalation process for data quality issues that are unclaimed, cross-domain, or exceed steward authority


to resolve.
• Gather steward feedback on alert quality and usability, feeding it back to the Data Quality Engineer for rule tuning.


Reporting, Adoption, and Communication
• Shape data quality dashboards and reporting around business subject areas so data owners can see clearly which


capability needs improvement.
• Produce recurring reporting on program effectiveness for leadership: subject-area quality and readiness scores,


rule coverage, alert volumes and trends, triage responsiveness, and open issue aging.
• Drive adoption and usability of the program: identify and cultivate the community of business consumers who


rely on data quality outputs, gather their feedback, and demonstrate the business value the program delivers
• Support organizational change management activities (communications, onboarding, stakeholder engagement)


as quality processes and dashboards roll out to business teams.
• Communicate program status, wins, and gaps to stakeholders in business-friendly terms.

Salary Range: $110,000 to $135,000 per year