HQ - Senior Analytics Engineer

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 — about governance and semantics as first-order concerns. We're close followers of where Analytics Engineering is going as a discipline. We're also honest about the realities: Job&Talent moves fast, our recruitment and workforce management platform is constantly evolving, and our data sources are moving targets. dbt projects grow organically in that environment, and ours shows it — improving it is part of the job.