About the role

Senior Analytics Engineer (Senior)

Build and own the trusted analytical layer of Collectors’ data platform—from warehouse data through transformations to the semantic layer.

Key Missions

Design & build data models and transformations using dbt on top of Google BigQuery.
Own the semantic layer in Lightdash, defining metrics, dimensions, and governed datasets for consistent answers.
Lead data modeling standards: set conventions, review practices, and documentation for the transformation layer.

Requirements

Modern data stack expertise across cloud warehousing (e.g., BigQuery), transformation, and workflow orchestration.
5+ years in analytics engineering, data engineering, or a similar role, with strong data modeling for reporting/analytics.
Expert in dbt with strong software engineering practices (e.g., modularity, testing, code review, documentation).
SQL + Python proficiency.
Experience with version control, CI/CD, and testing.
AI-assisted development: hands-on experience with Claude Code or similar coding agents, or strong desire to make AI-driven workflows core.
Cross-functional communication: translate business questions into well-modeled data and communicate with technical and non-technical stakeholders.
BI/semantic layer experience (e.g., Lightdash or Looker), with opinions on where the metrics layer is heading.
Analytical mindset: collect requirements, define and implement metrics, and build dashboards that tell a clear story.

Work Arrangement

Remote or hybrid.
Preference for candidates within one-hour commuting distance of an office.

About Collectors

Collectors builds a modern data platform and analytics layer that powers trusted reporting and metrics. The role focuses on turning raw warehouse data into governed semantic outputs for BI tools, using analytics engineering practices and a modern data stack.