Analytics Engineer

About this role

Data owns the pipelines, the warehouse and the definitions the business argues about — funnel conversion, time to hire, source quality.

Own the semantic layer between raw tables and the dashboards the business runs on, so that two teams asking the same question get the same answer.

The hard part is not the pipeline; it is that two teams asking the same question must get the same answer. Most of the work is in the semantic layer and in being willing to say a number is not trustworthy yet.

Primary responsibilities

• Own the transformation layer — the dbt models between raw data and everything the business reads
• Define the metrics the company argues about, write them down, and make the definition the one that is actually computed
• Test the models, so a broken assumption fails the build rather than the board deck
• Document the lineage so anyone can trace a number back to its source
• Work with analysts and stakeholders to turn a vague question into something a model can answer

Skills required

Day to day this role works with SQL, dbt and Data Modelling.

• Three or more years in analytics engineering or a very SQL-heavy analyst role
• Three or more years in analytics engineering or a strong analyst-plus-engineering background
• Expert SQL
• dbt in production, including testing and documentation
• Dimensional modelling and the discipline of a semantic layer
• Ability to turn a vague business question into something a model can answer

Preferred