Staff Analytics Engineer

About the role

tem is building AI native infrastructure to modernize electricity transactions and improve market transparency. As a Staff Analytics Engineer, you will design the domain models and semantic layers that power commercial, financial, and operational decisions across the company. You will work as an individual contributor to define technical standards and ensure our data infrastructure scales alongside our international expansion.

Key facts

What you'll do

• Establish and enforce high standards for testing, documentation, and modeling patterns across the organization.
• Develop a trusted domain layer that provides consistent context for both human users and AI agents.
• Collaborate with product managers, engineers, and sales teams to translate complex business requirements into reliable data models.
• Integrate new data sources and platform events to expand the reach of the analytics engineering function.
• Architect data systems capable of supporting global growth and new product offerings.
• Maintain the semantic layer to ensure metrics are defined accurately and used confidently across the business.

Requirements

• Proven experience building and refining domain layers in a production environment.
• Advanced proficiency in dbt, including custom macros and optimization of complex models.
• Strong SQL skills with experience managing data at scale in a modern warehouse.
• Hands-on experience with semantic layers or BI modeling tools such as Omni or Looker.
• High level of QA discipline and attention to detail when defining metrics and data structures.

Nice to have

• Background in energy markets or industries with significant physical or financial complexity.
• Experience managing commercial data, such as CRM pipelines, financial trading, risk, or forecasting.
• History of implementing quality standards or tooling that improved team-wide output.
• Ability to manage stakeholders by clarifying project scope and requirements early in the process.

Skills & tools

• dbt
• Airflow
• ClickHouse
• Omni (semantic layer)

Practical notes

The interview process typically spans 2 to 3 weeks and includes a talent screening, a behavioral interview with the Analytics Engineering Manager, a technical team exercise, and a final stakeholder discussion. We encourage applications from all backgrounds and welcome candidates who may not meet every listed requirement.