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PleoStaff Analytics Engineer
Pleo operates in the spend management sector, providing solutions designed to make money management effective for finance teams and employees. As the company expands, it is…
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About This Role
Pleo operates in the spend management sector, providing solutions designed to make money management effective for finance teams and employees. As the company expands, it is seeking a Staff Analytics Engineer to join its Data Services & Governance team on a full-time basis. In this senior individual contributor role, you will take ownership of the semantic layer, establish analytics and modeling standards, and champion AI-augmented development practices across all domains.…
Job Description
Pleo operates in the spend management sector, providing solutions designed to make money management effective for finance teams and employees. As the company expands, it is seeking a Staff Analytics Engineer to join its Data Services & Governance team on a full-time basis.
In this senior individual contributor role, you will take ownership of the semantic layer, establish analytics and modeling standards, and champion AI-augmented development practices across all domains. You will act as a technical leader without owning a single business domain, deciding and building the BI stack from the ground up while ensuring a single source of truth for AI agents, BI tools, and analysts.
This position is well-suited for professionals who enjoy building foundational architecture from the ground up, influencing teams through expertise rather than authority, and solving challenges related to making data legible for both analysts and AI agents. It is not a fit for candidates looking to manage a specific business domain or those who prefer maintaining an existing, mature infrastructure without contributing to tooling selections and foundational standards.
Responsibilities
- Own and define the semantic layer, including metric structures, definitions, and enforcement mechanisms across the organization
- Establish data modeling standards for clean, layered, and tested dbt architecture
- Build and direct the Analytics Engineering community of practice through documentation, code reviews, and onboarding
- Drive AI-native development practices by integrating AI coding tools into daily workflows for model writing, reviews, and migrations
- Partner with backend and product engineers upstream to encourage data contract discipline and schema ownership
- Contribute to internal and external customer-facing Data and AI Products
Requirements
- Demonstrated expertise in dbt and data modeling practices with the ability to define and enforce cross-functional architecture
- Extensive experience with BigQuery and SQL, addressing performance, cost, and complex analytical domains
- Prior hands-on experience owning a semantic layer such as LookML or dbt MetricFlow
- Practical experience using AI-native development tools like Claude Code or GitHub Copilot within a data engineering context
- Proven track record of establishing standards across independent teams through influence rather than direct authority
Core Skills
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the employment type for the Staff Analytics Engineer?
The position is full-time.
Is the location or remote status specified for this role?
The posting does not specify a location or a remote work status.
What does the interview process involve?
The interview process includes an introductory call with a Talent Partner, a technical core skills test, a 60-minute hiring manager interview, a live practical and technical Pleo Challenge, and a final 45-minute interview with a senior leader focusing on behavioral skills and values alignment.
What tech stack is currently used in the role?
The current technology stack includes GCP, BigQuery, dbt Core, Airflow, SQL, Python, Claude Code, and GitHub Copilot.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.