Analytics Engineer

Highlights

• Own the transformation layer between raw data and business decisions.
• Define certified metrics the entire company runs on.
• Build reusable data products served through AI agents.

What they offer

• Innovative culture with opportunity to define trajectory of AI
• Growth paths with opportunities to drive impact beyond immediate role
• Learning & development annual discretionary stipend
• Social travel annual discretionary stipend to meet colleagues
• Annual team offsite in a new location
• Monthly co-working stipend if not near main hubs

Ideal candidate

An experienced analytics engineer who thrives as an early owner, pairing rigorous data-quality instincts with strong stakeholder partnership to turn ambiguous questions into trusted metrics.

Requirements

• Demonstrated experience building and scaling a dbt project and metrics layer, ideally as one of the first analytics engineers on a growing team
• Expert knowledge of dbt and advanced SQL with strong grasp of dimensional modelling, grain and incremental patterns
• Proficiency across the modern data stack including BigQuery or similar warehouse, Python and BI tools such as Looker
• Rigour around data quality with testing, documentation and reconciliation by default
• Strong ability to understand varied stakeholder requirements, push back where needed and translate them into generalized, well-documented models
• Bonus: Experience modelling billing, subscription and ARR data (Stripe, Salesforce) or product event data at scale
• Bonus: Experience serving data to LLM-based agents or building semantic/metrics layers consumed by AI tools
• Bonus: Experience with CI for data (Slim CI, data contracts, PII policy tags) and infrastructure-as-code for warehouse access