Data Platform FinOps Specialist

必須

• Bachelor's Degree (BS) in Computer Science, Finance, Engineering, or a related field, or equivalent education and experience (7 years or more)
• Proficient in cloud FinOps, cloud billing analysis, or data platform cost management (4 years or more)
• Proficient with GCP billing - billing export to BigQuery, CUD/SUD mechanics, budget alerts, recommender API, and the Cloud Billing API (4 years or more)
• Proficient in SQL - writing complex billing queries and building dashboards from BigQuery billing export data (4 years or more)
• Proficient in building cost visibility dashboards using Looker Studio, Grafana, or equivalent BI tooling (3 years or more)
• Proficient in designing and presenting chargeback and showback models to finance and BU leadership (3 years or more)
• Proficient in Japanese at business level for BU finance reviews, vendor negotiations, and internal reporting (3 years or more)
• Proficient in English at professional level for cross-functional coordination (5 years or more)

歓迎

• Google Cloud Professional certification (Cloud Architect or Data Engineer) or FinOps Foundation Certified Practitioner
• Experience with Databricks cost management - DBU optimisation, cluster policies, and photon vs. standard compute (2 years or more)
• Experience with Snowflake cost governance - credit monitoring, warehouse scheduling, and resource monitors (2 years or more)
• Experience scripting in Python for billing API automation and anomaly detection (2 years or more)
• Experience in cloud financial management at enterprise scale (over $5M/year cloud spend) (2 years or more)
• Familiarity with GCP Dataplex cost metadata and tagging automation

使用ツール

Position Details

• As a Data Platform FinOps Specialist at Rakuten Group's Data Platform Department, you will drive the FinOps & Cost Optimisation function for data workloads - BigQuery, Databricks, Azure, and Snowflake - across over 70 business units. You will build cost-visibility dashboards, operate the monthly FinOps review cycle, implement GCP committed-use discount strategies, and translate spend data into actionable optimisation recommendations that directly reduce platform unit costs.
• Build and maintain cost visibility dashboards covering BigQuery (slots and on-demand), Databricks DBU, and Snowflake credit consumption, broken down by BU, team, project, and workload
• Own the spend attribution model - implement chargeback and showback frameworks so BU finance teams can see and own their data platform costs
• Identify and act on GCP CUD (Committed Use Discount) optimisation: analyse slot commitment vs. on-demand patterns and recommend right-sizing and reservation changes
• Run monthly unused-asset cleanup cycles: identify idle datasets, dormant pipelines, and over-provisioned clusters, and coordinate decommission with data owners
• Operate the monthly FinOps review with BU finance stakeholders - prepare spend summaries, variance analysis, and savings tracking
• Instrument GCP billing APIs and Dataplex cost metadata to automate cost tagging and anomaly alerting
• Partner with the Platform Engineering team to embed FinOps guardrails in CI/CD pipeline templates (cost estimation pre-deploy, budget alerts)
• Contribute to the platform unit economics model - cost per query, cost per pipeline run, and cost per BU workspace