Staff Analytics Engineer

This is a fully remote position, open to applicants in United Kingdom, +3 more states.

📋 Description

• Take ownership of and define Pleo's semantic layer, encompassing metric definitions, structure, location, and enforcement.

• Establish data modeling standards throughout the Analytics Engineering function by utilizing a clean, layered, and well-tested dbt architecture.

• Develop and manage the Analytics Engineering community of practice through code reviews, shared patterns, documentation, and onboarding processes.

• Lead AI-native development practices for the creation, review, and migration of data models.

• Assess AI coding tools, oversee associated risks, and guide their adoption within the Analytics Engineering community.

• Spearhead AI-enhanced migration efforts throughout the Analytics Warehouse and Operational Data Platform.

• Design structured data models and metric definitions to ensure reliable AI-service consumption.

• Collaborate with backend and product engineers to enhance upstream data contracts and ownership of schemas.

• Contribute to external customer-facing Data & AI Products, including conversational analytics capabilities.

• Analyze current modeling standards and identify gaps in the semantic layer during the initial six months.

• Participate in decisions regarding semantic-layer tooling and onboard Analytics Engineers through documentation, live sessions, and PR reviews.

⛳️ Requirements

• Extensive and demonstrated expertise in dbt and data modeling practices.

• In-depth knowledge of BigQuery and SQL, including performance, cost considerations, and complex analytical-domain architecture.

• Proven experience managing a semantic layer using LookML, dbt MetricFlow, or a comparable tool.

• Authentic AI-native development experience in a data engineering context, utilizing tools such as Claude Code, GitHub Copilot, or similar.

• A successful history of establishing and enforcing standards across teams without direct managerial authority.

• Understanding of LLM and agentic-tool requirements relevant to data modeling, documentation, and metric definitions.

• Demonstrated experience engaging with backend engineers on data contracts and senior stakeholders regarding semantic-layer strategy.

• Experience leading technical initiatives with organization-wide or cross-team impacts within a technology company of 500–1000+ employees.

• Prior ownership of a semantic layer is essential.

• Proficiency in English for application and use as the primary company language.

🏝️ Benefits

• Flexible remote work arrangement.

• Accessibility support and an interview process tailored to candidates' needs.

• Comprehensive review of every application by a human reviewer.

• Opportunity to collaborate with a diverse team of over 850 individuals from more than 100 nationalities.