Staff Data Platform Engineer, Yoto

• Extensive hands-on experience in data engineering or analytics engineering, with a demonstrable track record of owning platform-level systems end-to-end, not just individual pipelines
• Experience designing and operating production data platforms across cloud infrastructure, orchestration, ingestion and SQL transformation layers
• Practical experience with GCP, BigQuery, Terraform, Kubernetes, Dagster, dlt and dbt - or equivalent tools with the ability to articulate transferable reasoning
• Demonstrated ability to make and document architecture decisions that involve meaningful trade-offs across multiple teams or domains
• A track record of authoring and landing technical standards across Python, SQL and infrastructure code that other engineers, analysts and data scientists adopt in their day-to-day work
• Experience defining the scope of ambiguous technical problems - identifying what needs to be built and why, not just executing against an existing spec

Desirable

• We’re looking for a Staff Data Platform Engineer to join our Data team at Yoto, to help power insights and decision-making across the business
• You'll set technical direction, raise the engineering bar across the data team, and shape how our data platform scales as Yoto grows
• We’re a growing team at the heart of all the decisions Yoto makes. We tackle a broad range of problems, from developing cutting edge data solutions to building and maintaining data pipelines, query and orchestration platforms, our work spans across all the key strategic projects throughout the company
• We supercharge growth by providing self-service tools, valuable insights and advanced data science solutions. We work in a high-trust environment with a lot of independence. Everyone can contribute ideas and be part of the decision making process
• Own the architecture, reliability and long-term health of Yoto's end-to-end data platform, spanning GKE-hosted infrastructure, data ingestion, orchestration and transformation
• Define and maintain the data platform roadmap, translating company strategy into a sequenced set of technical investments with clear short- and long-term trade-offs documented
• Work across data science, analytics, product and software engineering to convert business requirements into platform capabilities, and ensure the platform serves company-wide use cases
• Set and enforce standards for data governance, access controls, data quality and ownership across the platform
• Manage and develop a mid-level data engineer directly, including regular 1:1s, performance reviews, and structured growth plans, while also raising technical capability across the wider data team through code review, documentation and pairing