Own the onboarding and ongoing maintenance of data sources, keeping them reliable and trusted by the business and resolving issues in partnership with engineering

Apply ETL best practices to define pipeline structure, and partner with data engineering to specify pipelines to be built or modified

Own the data dictionary, maintaining consistent dimension and metric definitions across the business

Lead validation efforts and establish data quality checks that keep reporting accurate and reliable

Lead exploratory analyses across traffic, audience, and revenue performance, and synthesize analyst findings into the most significant insights for executive stakeholders and the data director

Partner with product, engineering, content, and revenue leaders to scope questions, shape priorities, and present findings so audiences leave with clear takeaways, not just data

Build, maintain, and enhance dashboards and reports that support business stakeholders

Set reporting standards and best practices, and share expertise with fellow analysts through reviews, documentation, and informal guidance

Analytics Expertise: Deep understanding of engagement metrics, funnels, and KPIs, with familiarity in both traffic and revenue performance reporting. Advanced SQL (BigQuery) and Python for querying and analyzing complex, multi-source datasets.

Data Pipelines: Understanding of ETL concepts and best practices, with the ability to write clear technical requirements (e.g., in JIRA) for engineers.

BI & Analytics Platforms: Advanced experience with Power BI, Looker, or similar tools, and strong proficiency in GA4 or similar tools (e.g., Adobe Analytics).

Familiarity with Google Cloud Platform beyond BigQuery, and Azure

Senior Product Data Analyst - Digital Analytics

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Hearst

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