Senior Data Engineer

Description:

We're looking for a Senior Data Engineer to join our Growth Intelligence team at Pleo. In this role, you'll design and maintain the integration architecture and data contracts that connect our commercial and GTM data layer (the pipelines linking our CRM, billing, and customer success tooling to a central BigQuery warehouse) and be part of the team as we scale our commercial data foundations to support RevOps, Customer Success, and the AI products built on top of them. If you're excited about untangling complex, multi-system architecture and are passionate about building data foundations the whole business can trust, then this is the opportunity for you!

Who You’ll Be Working With And Reporting To

You’ll report to the Senior Manager of Growth Intelligence and work closely with the RevOps and the BAT (Business Architecture & Technology) teams to understand what commercial operations needs from data. Our team is highly collaborative and dedicated to keeping Pleo's commercial and GTM data trustworthy and well-governed. You’ll also partner with Analytics Engineers to ensure pipeline outputs are modelling-ready, and engage upstream with tool owners and engineering teams to push data quality and schema discipline closer to the source.

What You’ll Be Doing

As a Senior Data Engineer, you will:
 

• Design, build, and maintain data pipelines between commercial tools (HubSpot, Zuora, Vitally) and our BigQuery data warehouse.
• Own reverse ETL flows: enrich or define data in the warehouse and push it back into operational tools like HubSpot, keeping definitions consistent across systems.
• Implement and maintain data contracts with clear ownership, SLAs, and schema agreements between data producers (tool owners, product engineers) and data consumers (analysts, RevOps, AI tooling).
• Partner with RevOps and the BAT team to understand operational data requirements and translate them into reliable, governed pipelines.
• Build monitoring and alerting that catches data quality issues before they surface in dashboards, operational reports, or downstream models.
• Simplify integration architecture by centralising data flows through the warehouse, reducing point-to-point tool integrations and the maintenance burden that comes with them.
• Work with Analytics Engineers to ensure pipeline outputs are structured and documented for downstream modelling.
• Engage upstream with tool owners and engineering teams to move data quality and schema discipline closer to the source.
   

Our commercial data stack connects subscription billing (Zuora), CRM (HubSpot), and customer success tooling (Vitally) to a central BigQuery data warehouse. You can expect to work with the following tech stack: BigQuery, Python, HubSpot, Zuora, and Vitally plus dbt, Fivetran/Census, or Airflow depending on your background.

What You Bring

You’ll thrive in this role if you have:
 

• Proven experience building and maintaining production data pipelines in a commercial or GTM data environment.
• Strong understanding of CRM data models, APIs, and field management (HubSpot or comparable experience).
• Hands-on experience with reverse ETL patterns: pushing warehouse-enriched or warehouse-defined data back into operational tools.
• Extensive BigQuery experience.
• Experience implementing data contracts in a production environment.
• Python proficiency for pipeline development, transformation logic, and tooling.
• Git-based workflows and CI/CD experience for data engineering code.