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HQ - Senior Analytics Engineer

Job&Talent - Madrid HQ, ES

Posted Apr 29, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Market context

Median wage (BLS OEWS)
$111,944 national median
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work
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Application

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Deadline
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Where they hire

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About this role

HQ - Senior Analytics Engineer Madrid HQ, ES Join us to shape the future of work: your next adventure awaits! The role We're a small, well-established Analytics Engineering team sitting inside the HQ Data Team and serving the rest of the business - Finance; Product Strategy; Go-to-Market; Sales, Branding, and Marketing; and Software Engineering. We've recently completed our migration from Redshift to BigQuery, and we're adopting dbt Fusion. The development loop runs through the official dbt VS Code extension and dbt-lsp. Looker is our BI layer; dbt Elementary backs our observability. Alongside the day-to-day modelling work, we're assembling an agentic layer over the codebases and collaboration tools we interact with - dbt, BigQuery, Airflow, Terraform, GitHub, Jira, Notion, and Slack. The team uses Claude Code, and we are building an internal plugin marketplace of skills, commands, and agents for our work. We expect this kind of tooling-driven leverage to become a defining part of Analytics Engineering, and we'd rather be in front of that shift than carried along by it. We want someone who's excited to be in the middle of it - not just a consumer of AI tools, but someone who can help shape what the team builds. This is a role for someone who treats Analytics Engineering as a craft. We care about modelling clarity, performance and accuracy, documentation that's actually useful, and codebases that age well. We care about the meaning and value of the data we handle, not just the pipes that move it -

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