Senior People Analytics Analyst (Remote) - 1079

Job Description: As a Senior Analyst on the People Insights & Engineering (PIE) team, you'll help sustain and advance the data infrastructure, business intelligence, and reporting that Etsy's people analytics run on. This is a hands-on delivery role focused on execution and infrastructure progression, working closely with — and under the direction of — the PIE technical lead. Your work will keep our governed analytics environment running while moving key infrastructure forward.

The Senior Analyst will be responsible for:

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• Delivering recurring and clearly-scoped reporting, and identifying, analyzing, and interpreting trends across disparate data sources.
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• Building and extending canonical people data tables (BigQuery / dbt) to support governed analytics and agentic/LLM use, under the direction of the PIE technical lead.
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• Supporting warehouse and data-modeling work in partnership with the PIE technical lead — e.g., informing backfill strategy, reviewing org/hierarchy mapping, and evaluating data-quality checks.
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• Migrating, maintaining, and enhancing existing governed dashboards as part of our BI tooling migration, ensuring metric consistency with the governed layer.
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• Running and improving the market/compensation benchmark data extraction process (e.g., Radford, Mercer).
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The Senior Analyst will demonstrate:

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• 3+ years of HR/people analytics reporting experience, ideally at a fast-growing company.
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• Strong SQL for reporting, data manipulation, and modeling.
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• Hands-on experience with a cloud data warehouse (BigQuery preferred).
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• Experience with dbt or a comparable data transformation/modeling tool (preferred).
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• Experience working with version control systems (git/github).
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• Proficiency with BI/dashboarding tools (Looker preferred; Tableau, Power BI, etc.); LookML a plus.
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• Experience with R or Python for data analysis/visualization (preferred).
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• Experience using modern LLM tools (e.g., Claude Code) as a productivity multiplier and quality enhancer (preferred).
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• Experience working with data from disparate sources of varying quality.
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• Working knowledge of data privacy best practices for employee/people data.
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• Working knowledge of canonical HR functions (Talent Acquisition, Operations, Development, etc.).
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