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The Databricks Platform Engineer contributes to the design, implementation, and maintenance of core automation systems and the observability layer for a new Databricks-based data platform. The role builds and operates contract-driven deployment pipelines, governance automation, monitoring, and platform health signals.
応募資格
必須
- 5+ years of experience in data engineering, data platform engineering, or DataOps.
- 3+ years of experience with the Databricks platform: Unity Catalog, workspace administration, Databricks SDK, and REST APIs.
- Strong proficiency in Python: automation scripting, YAML parsing, code generation, and API integration.
- Solid software engineering practices: modular design, code maintainability, error handling, testing, and documentation.
- Experience with Declarative Automation Bundles or equivalent infrastructure-as-code deployment frameworks for Databricks.
- Understanding of RBAC and governance models: schemas, grants, column masks, row filters.
- Experience with CI/CD pipelines (Azure DevOps and Azure Pipelines favored): multi-stage YAML pipelines, environment approvals, service connections.
- Experience building monitoring dashboards, alerting systems, and operational reporting.
歓迎
- Proficiency in SQL.
- Familiarity with the Open Data Contract Standard (ODCS) or similar data contract frameworks.
- Experience with Delta Lake internals: transaction log analysis, write audit trails, schema evolution.
- Experience with data quality frameworks and SLA/SLO monitoring.
- Knowledge of Azure Entra ID, SCIM provisioning, or workload identity federation.
- Experience with Git workflow design: branching strategies, merge policies, environment promotion.
- Experience in IT operations domains such as license management or asset management.
- English: Business Level
- Japanese: Preferred
求める人物像
- A hands-on engineer with a get-things-done attitude.
- Passionate about data-driven decision making, process improvement, and operational excellence.
- A collaborative problem-solver who builds shared understanding before committing to a technical direction.
- Understands how platform design decisions impact the domains and teams that depend on the platform.
- Rigorous about deployment safety: atomicity, rollback, idempotency, and testing.
- Comfortable working with high standards of governance.
- Understands the importance of measuring platform health signals and operational visibility from the start, not as an afterthought.
- Effective at balancing long-running platform build work with responsive operational monitoring duties.
募集要項最終確認 10/2
- 職種
- プラットフォームエンジニア
- 雇用形態
- 記載なし
- 給与
- 記載なし
- 勤務地
- 東京都
- 働き方
- 記載なし
- 経験年数
- 3年以上
- 掲載日
- 2026/09/29 22:03（3日前）
- 最終確認
- 2026/10/02 04:47（今日）
仕事内容
Why We Hire
- As Rakuten continues to expand its data-driven capabilities with a new Databricks-based data platform, we need a hands-on engineer who can contribute to the design, implementation, and maintenance of the platform's core automation systems and observability layer.
- This role is critical for the success of the project: the data contract-driven deployment pipeline, the Declarative Automation Bundle generation system, and the monitoring infrastructure that ensures platform health and SLA compliance. It requires a Databricks Platform Engineer who combines deep Databricks and Python expertise with strong software engineering capabilities.
- The successful candidate will proactively identify design challenges across systems with no internal precedent and propose well-reasoned solutions for team review. They will bring a methodical engineering approach to the full build-and-operate cycle, from contract processing to production monitoring, ensuring the sustainability and scalability of the platform's systems and processes.
Position Details
- Design and implement the contract-driven Declarative Automation Bundle generator that translates Open Data Contract Standard YAML files into deployable Databricks assets.
- Build and maintain the Declarative Automation Bundle deployment pipeline, including environment parameterization, deployment atomicity, and rollback mechanisms.
- Develop and operate Azure Pipelines CI/CD workflows: multi-stage pipelines, environment approvals, variable groups, and service connections.
- Implement Unity Catalog governance automation: schema, table, tag, and grant management via Databricks SDK and REST APIs.
- Generate and execute SQL DDL statements for column masks and row filters as defined by data contracts.
- Design and maintain the contract index, including atomic maintenance and recovery mechanisms.
- Implement the dead-letter asset pattern: co-deployment generation and deployment atomicity.
- Design and enforce Git workflows: branching strategies (develop/staging/main), merge policies, and environment promotion gates.
- Develop schema validation, smoke tests, and idempotent deployment verification.
- Build platform health dashboards and alerting from Databricks system tables.
- Design and implement freshness signals via Delta transaction log analysis.
- Implement SLA/SLO comparison logic against contract-declared commitments using the contract index.
- Build dead-letter accumulation SLI monitoring for mandated platform signals.
- Design platform health signal monitoring: SCIM sync latency, deployment ordering failure detection, break-glass activation alerting.
- Develop cost attribution reporting.
- Implement data quality monitoring using Unity Catalog quality constraints and expectation-based frameworks.
- Contribute to Databricks workspace deployment and administration alongside the Cloud Platform Engineers.
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