Analytics Engineer

Analytics Engineer

Summary

We are looking for a technically sharp Analyst to join our data team. This role sits squarely at the intersection of data engineering and analytics — you''ll work at the lowest level of detail alongside our engineering team to pull in and model data, while also being able to structure that detail into the high-level insights that drive business decisions. You''ll partner with stakeholders to understand their needs, translate business questions into well-scoped analytic products, and build the logic end-to-end to make it happen. This is a largely technical role, but you should be comfortable driving your own projects with minimal oversight — identifying blockers, making pragmatic decisions, and delivering with quality.

Responsibilities

Design, build, and maintain scalable data models using dbt (preferred) or a comparable data modeling framework (e.g. redshift SQL, postgres)

Write, optimize, and debug SQL to transform raw source data into reliable, reusable datasets.

Collaborate closely with data engineering to understand upstream sources, support data ingestion efforts, and ensure data quality end-to-end.

Partner with stakeholders to gather requirements, define analytic scope, and translate business needs into quantifiable analytic products.

Version all work using Git, maintaining high standards for code quality, documentation, and reproducibility.

Manage your own projects with limited oversight — proactively surfacing issues, aligning stakeholders, and driving work to completion.

Qualifications

4+ years of experience in an analytics engineering or data analytics

Expert-level SQL skills — you can write, optimize, and debug complex queries across large, messy datasets.

Experience with dbt (preferred) or another data modeling tool.

Comfortable working with Git and version-controlled analytical workflows.

Ability to work at the granular level with engineering teams and at the summary level with business stakeholders — you''re equally at home in both contexts.

Strong project ownership: able to define scope, drive execution, and deliver results with minimal hand-holding.

Clear communicator who can translate technical concepts for non-technical audiences.

An AI-forward mindset — you relentlessly look for ways to use AI-assisted tools to automate the routine, accelerate your work, and punch above your weight as an individual contributor.

Proficiency with at least one major BI tool — Looker, Tableau, Power BI, or equivalent (nice to have, not a requirement)