Data Product Analyst

Act as the Data Subject Matter Expert to stakeholders, building deep knowledge of international data across the end‑to‑end data supply chain through hands-on work on every intake and production incident

Make international data trustworthy by working directly with business and marketing stakeholders to resolve data issues and build their confidence in the data.

Query, trace, and validate data from multiple sources to investigate anomalies, answer ad hoc requests, and uncover trends, patterns, and actionable insights.

Translate analytical findings into clear, business friendly insights that support decision‑making. Go beyond producing numbers: state what they mean in a sentence and anticipate the stakeholder's next question.

Elicit, document, and manage business, functional, and nonfunctional requirements through techniques such as interviews, workshops, process analysis, and user story creation. Write complete intakes that capture every requirement in as much detail as possible.

Own delivery after handoff: check in regularly with data engineering, confirm that what is built matches what was requested, and drive issues to resolution without waiting for direction.

Support prioritization by assessing business value, impacts, complexity, and risk.

Ensure traceability of requirements from intake through development, testing, and deployment.

Collaborate with data engineering analysts, architects, and engineers to ensure solutions reflect business context and use cases.

Define acceptance and UAT criteria that go beyond what the business specifies, including data accuracy, completeness, and edge cases; support user validation and provide structured feedback for continuous improvement.

Monitor and enhance data quality through profiling, validation, remediation, and alignment with organizational priorities.

Build and maintain business-rule monitors and alerts that catch business logic issues engineering's technical checks may miss, and review past incidents to close monitoring gaps.

Participate in PSG and release go/no-go meetings to stay informed on production changes that may affect data quality or reporting.

Manage time and availability: decide which meetings need active participation versus a recording and raise calendar overload or availability issues early.