Data Platform FinOps Specialist - Data Platform Department (DPD)

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.

<Responsibilities>

・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

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Languages:

English (Overall - 3 - Advanced), Japanese (Overall - 3 - Advanced)