Analytics Engineer (AI)

TL;DR

Analytics Engineer (dbt/ClickHouse): Building and optimizing the semantic and domain layers for an AI-native energy transaction infrastructure with an accent on data trust and scalability. Focus on developing complex dbt models, optimizing warehouse performance, and creating high-fidelity context for AI agents.

Location: Remote (Europe)

Salary: £115K + Equity

Company

hirify.global is rebuilding energy transaction infrastructure using AI to make electricity markets transparent, fair, and efficient.

What you will do

• Set and raise the bar for analytics engineering standards, defining patterns, testing, and review practices for dbt models.
• Own the semantic layer (Omni) and underlying domain models to provide trusted data for humans and AI agents.
• Build a first-principles domain model that powers commercial, financial, risk, and operational decisions.
• Integrate new data sources and platform events to expand analytics engineering's reach across the organization.
• Partner with engineers, product managers, and sales teams to translate business needs into concrete data outputs.

Requirements

• Proven experience building or reworking a domain layer at scale.
• Deep production expertise with dbt, including custom macros and optimization of expensive models.
• Excellent SQL skills and experience with modern data warehouses, specifically ClickHouse.
• Hands-on experience with semantic layers or BI modelling tools such as Omni or Looker.
• Strong QA discipline and a meticulous eye for detail.
• Must be based in Europe.

Nice to have

• Experience with commercial data (CRM pipelines), financial trading data, or risk and time-series modelling.
• Track record of implementing quality standards that measurably improved team output.
• Strong first-principles stakeholder management skills.
• Experience in the energy sector or other industries with high physical or financial complexity.

Culture & Benefits

• Competitive salary with equity offers.
• Direct technical ownership and influence over company-wide metric definitions.
• Opportunity to work in a fast-scaling, AI-native startup environment.
• Collaborative, cross-functional work culture with high impact.

Hiring process

• Initial 30-minute call with the Talent Team.
• 75-minute behavioral interview with the Analytics Engineering Manager.
• 60-minute technical interview with peers involving a live technical exercise.
• 45-minute "Bar Raise" interview with cross-functional stakeholders.