Data Platform Engineer

About the role

As a Platform Engineer within B2Spin's Business Intelligence team, you will own the foundational infrastructure that powers the company's data platform. You will design, build, and maintain secure, observable, and scalable systems so that data engineers can focus on delivering insights rather than fighting infrastructure.

Key responsibilities

• Provision and manage development, staging, and production data environments using Infrastructure as Code, ensuring consistency and eliminating drift.
• Design and enforce IAM policies, role‑based access controls, secrets rotation, and secure provisioning for external BI tools such as Looker and Tableau.
• Configure GitLab runners and automated CI/CD pipelines tailored for data workflows, maintaining clean integrations across repositories, warehouses, orchestration frameworks, and analytics tools.
• Implement observability frameworks that provide proactive alerting and fast root‑cause analysis across all pipelines and infrastructure.
• Audit resource utilisation, establish cost‑allocation tagging, optimise spend, and maintain disaster‑recovery readiness.
• Act as the bridge between Data Engineering, Core Infrastructure, and IT, unblocking engineers to ship quickly and securely.

Required profile

• Solid hands‑on experience with Infrastructure as Code tools (Terraform, Pulumi, or equivalent) in a data or analytics platform context.
• Proven depth in cloud IAM, secrets management, and security hardening across data platform environments.
• Confident operating CI/CD pipelines—particularly GitLab—tailored for data engineering workflows.
• Familiarity with modern data‑stack integrations: cloud data warehouses (BigQuery, Snowflake, Redshift), orchestration tools, and BI platforms.
• Experience implementing observability and monitoring solutions for data infrastructure.
• Track record of cost governance, including auditing cloud spend, tagging resources, and recommending optimisations.

Required skills

• Terraform
• Pulumi
• GitLab (runners, CI/CD pipelines)
• BigQuery
• Snowflake
• Redshift
• Looker
• Tableau
• IAM (cloud identity and access management)
• Secrets management
• Observability
• Monitoring
• Cost‑allocation tagging