Data Platform FinOps Specialist - Data Platform Department (DPD)
- 雇用形態
- Full Time
- 勤務形態
- Hybrid
- 給与
- 記載なし
この仕事について
仕事内容は掲載元の言語で表示しています。最新の条件は企業の募集ページでご確認ください。
Job Description:
Business Overview
The Technology Platforms Division (TPD) drives the growth of Rakuten's ecosystem by delivering innovative, high-quality technology platforms characterized by integrated control and strategic partnerships.
Within TPD, the Cloud Platform Supervisory Department (CPSD) develops and manages Rakuten's state-of-the-art cloud platform, empowering global scalability and accelerating innovation across its diverse business units.
Department Overview
The Data Platform Department (DPD) at Rakuten Group develops and maintains a comprehensive data platform, empowering over 70 Rakuten services with solutions for data ingestion, discovery, governance, analytics, and querying. We support data-driven decision-making across one of Japan's largest data ecosystems, providing the tools and infrastructure to support key domains such as Data Lakes, Data Warehouses, and Business Intelligence.
Position:
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
Mandatory
Qualifications:
- 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)
- Desired
Qualifications:
- 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
- #engineer #applicationsengineer #technologyplatformdiv
- Languages:
- English (Overall - 3 - Advanced), Japanese (Overall - 3 - Advanced)
応募要件
- 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)
- 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
- #engineer #applicationsengineer #technologyplatformdiv
必要なスキル
- Azure