Analytics Engineer

Messy spend management is tricky business. And tedious processes are a lose-lose situation for all involved, not just finance. We build spend solutions that make managing money seamless, empowering, and surprisingly effective for finance teams and employees alike - with a vision to help all businesses ‘go beyond’.

• Python Our tech stack currently include: GCP, Big Query, dbt Core, Airflow, SQL, Python, Claude Code, Git Hub Copilot. must have
• SQL Deep Big Query and SQL expertise, including performance, cost considerations, and the architectural challenges of complex analytical domains. must have
• dbt Deep demonstrated expertise in dbt and modelling practices: not just strong modelling, but a formed view of what modelling architecture should look like across a function. must have
• GCP Our tech stack currently include: GCP, Big Query, dbt Core, Airflow, SQL, Python, Claude Code, Git Hub Copilot. must have
  · not practised here
• Airflow / orchestration Our BI stack is also in transition so, you would not be inheriting a mature setup and maintaining it.
• - Set data modelling standards for the function: what clean, layered, well-tested dbt architecture looks like across all domains, at all levels of complexity.
• Governance & security This is a senior individual contributor role in our Data Services & Governance team where you'll act as the thought and technical leader owning the semantic layer and analytics standards for Pleo. not practised here
• - Engage upstream with backend and product engineers to drive data contract discipline and schema ownership upstream, rather than managing inconsistency downstream.
• The semantic layer you will be designing and maintaining will be the single source of truth that AI agents, BI tools, and analysts query. not practised here
• Cost & performance
  - Deep Big Query and SQL expertise, including performance, cost considerations, and the architectural challenges of complex analytical domains.
• Warehousing
  - Lead responsible AI-augmented migration work using AI tooling to accelerate data modelling and migrations across the Analytics Warehouse and Operational Data Platform.
• Machine learning You'll report to the Data Engineering Manager who oversees the Data Infra & MLOps team as well as the Data Services & Governance team. not practised here