Remote opportunity at
PleoAnalytics Engineer
Pleo operates in the spend management sector, developing solutions intended to make handling money straightforward and effective for organizations and their employees alike. The company maintains…
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About This Role
Pleo operates in the spend management sector, developing solutions intended to make handling money straightforward and effective for organizations and their employees alike. The company maintains an international team distributed across multiple nations. Pleo is hiring an Analytics Engineer to join its Product Intelligence team. This position involves owning the data modelling layer that supports product behaviour, go-to-market performance, commercial data science, financial reporting, and operational intelligence. The person in…
Job Description
Pleo operates in the spend management sector, developing solutions intended to make handling money straightforward and effective for organizations and their employees alike. The company maintains an international team distributed across multiple nations.
Pleo is hiring an Analytics Engineer to join its Product Intelligence team. This position involves owning the data modelling layer that supports product behaviour, go-to-market performance, commercial data science, financial reporting, and operational intelligence. The person in this role will build tracking, experimentation, and data modelling foundations to ensure product data is reliable and accessible for self-service. Responsibilities include migrating the analytics stack to a new Analytics Warehouse and Omni tool, moving away from legacy platforms such as Looker and Hippocampus.
This role suits professionals who want to build the infrastructure driving product decisions rather than merely reporting on existing data. Candidates should possess strong SQL and dbt skills, experience with event-based tracking instruments, and familiarity with Git workflows. The recruitment process includes an initial call, a SQL test, a hiring manager discussion, a team interview featuring a live data modelling case, and a final meeting with the VP of Data & AI.
Responsibilities
- Build and maintain dbt models within the new Analytics Warehouse using a layered architecture.
- Manage tracking plan execution and quality assurance directly in Segment and Amplitude.
- Model assignment and outcome data into structured formats to support experimentation.
- Establish and document metric definitions inside the semantic layer for consistent reporting.
- Utilize AI-augmented data modelling practices during code writing, review, and migration tasks.
- Collaborate with product managers and analysts to convert one-off questions into reusable data models.
- Preserve data quality through dbt tests, freshness SLAs, and proactive monitoring.
Requirements
- Solid experience with SQL and dbt for end-to-end model ownership.
- Working knowledge of event-based tracking systems like Segment or Amplitude.
- Familiarity with Git-based development workflows, including opening and reviewing pull requests.
- Day-to-day utilization of AI tooling as part of coding and workflow routines.
- Ability to navigate ambiguity and refactor legacy logic.
Core Skills
Benefits
- Personal Pleo card for business expenses without out-of-pocket spending
- Lunch provision through catered meals or a local office lunch allowance on work days
- Comprehensive private healthcare options depending on location
- 25 days of annual holiday plus public holidays, with the option to purchase 5 additional days through salary sacrifice
- Flexible working arrangements supporting hybrid and fully remote setups
- Free mental health and well-being support through MyndUp
- Paid parental leave policies
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the remote work policy for this role?
The posting indicates flexible working options supporting fully remote setups.
What is the salary for the Analytics Engineer position?
The salary is not stated in the job posting.
What does the interview process involve?
The interview process consists of an introductory call with a talent partner, a SQL test via CoderPad, an interview with the data and analytics manager, a team interview and live case via CodeSignal, and a final meeting with the VP of Data & AI.
What technologies are used in the data stack?
The tech stack includes GCP BigQuery for the data warehouse, dbt for transformation, Airflow for orchestration, Segment and Amplitude for tracking, Omni for BI and analytics, and SQL as the language.
Sample Interview Questions
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