#126292 - 高级 FinOps 数据工程师
#126292 - Senior FinOps Data Engineer
我们正在寻找一位高级FinOps数据工程师，负责设计、构建和维护支持云成本透明度、归因和优化的数据采集、自动化和分析平台。
该职位将处理大规模的账单、使用情况、遥测、性能和财务数据。工作内容将使产品、工程、分析和财务相关方能够更快地做出数据驱动的决策，并信任底层数据。理想的候选人是一位当前从事数据工程工作的技术人员，能够构建生产环境的数据流水线和以成本为导向的数据产品，提升其长期可维护性，并能向技术和非技术受众清晰解释其技术决策。
主要职责
- 在云环境中设计、构建和维护可靠的端到端ELT和ETL流水线。
- 开发用于基于遥测的成本归因和基于性能的财务建模的工具和数据集。
- 构建和维护提供云成本透明度、识别优化机会并支持承诺使用折扣建模和管理的流水线和自动化。
- 从云平台、API和其他来源中采集和对齐大规模的账单、使用情况、遥测和性能数据。
- 设计和成熟支持可靠下游分析和报告的数据模型、模式和采集框架。
- 提升生产数据工作流的可维护性、可扩展性、可观测性和可靠性。
- 实现全面的数据审计、验证、对账和端到端质量控制。
- 构建和维护REST API集成和基础设施自动化。
- 支持CI/CD开发流程和使用Terraform的基础设施即代码（IaC）。
- 排查生产流水线故障、数据不一致性和性能问题。
- 与产品、工程、分析和财务相关方合作，将技术数据转化为清晰、可操作的见解。
必备技能
- 熟练使用SQL、Python、Spark和Scala。
- 熟练使用工作流编排工具，如dbt、Airflow和Dagster。
- 熟练使用AWS，包括AWS Glue、Amazon Aurora和Amazon Athena。AWS经验是必需的。
- 熟练使用GCP和Snowflake。
- 有架构和改进端到端ELT和ETL数据流水线长期可维护性的经验。
- 强大的数据建模经验，包括模式设计和模式成熟度。
- 有...
查看英文原文
We are seeking a Senior FinOps Data Engineer to design, build, and maintain the data ingestion, automation, and analytical platforms that support cloud cost transparency, attribution, and optimization.
This role will work with large-scale billing, usage, telemetry, performance, and financial data. The work will enable Product, Engineering, Analytics, and Finance stakeholders to make faster, data-driven decisions and trust the underlying data. The ideal candidate is a current, hands-on data engineer who can build production data pipelines and cost-focused data products, improve their long-term maintainability, and clearly explain their technical decisions to both technical and non-technical audiences.
Key Responsibilities
- Design, build, and maintain reliable end-to-end ELT and ETL pipelines in cloud environments.
- Develop tooling and datasets for telemetry-driven cost attribution and performance-informed financial modeling.
- Build and maintain pipelines and automation that provide cloud cost transparency, identify optimization opportunities, and support committed-use discount modeling and management.
- Ingest and reconcile large-scale billing, usage, telemetry, and performance data from cloud platforms, APIs, and other sources.
- Design and mature data models, schemas, and ingestion frameworks that support reliable downstream analysis and reporting.
- Improve the maintainability, scalability, observability, and reliability of production data workflows.
- Implement comprehensive data auditing, validation, reconciliation, and end-to-end quality controls.
- Build and maintain REST API integrations and infrastructure automation.
- Support CI/CD development processes and Infrastructure as Code using Terraform.
- Troubleshoot production pipeline failures, data inconsistencies, and performance issues.
- Partner with Product, Engineering, Analytics, and Finance stakeholders to translate technical data into clear, actionable insights.
Must-Have Skills
- Hands-on experience with SQL, Python, Spark, and Scala.
- Hands-on experience with workflow orchestration tools such as dbt, Airflow, and Dagster.
- Hands-on AWS experience, including AWS Glue, Amazon Aurora, and Amazon Athena. AWS experience is required.
- Hands-on experience with GCP and Snowflake.
- Experience architecting and improving the long-term maintainability of end-to-end ELT and ETL data pipelines.
- Strong data modeling experience, including schema design and schema maturity.
- Experience processing, validating, and auditing data at scale.
- Exposure to CI/CD development processes and version control.
- Infrastructure as Code experience using Terraform.
- REST API programming and data-integration experience.
- Strong attention to detail, analytical ability, and production troubleshooting skills.
- Ability to explain technical concepts and personally delivered work clearly to non-technical audiences.
Nice-to-Have Skills
- Experience working with FinOps teams or performing cloud cost-optimization duties.
- FinOps Certified Practitioner or FinOps Certified Engineer certification.
- Experience working with Datadog API endpoints.
- Experience with Go.
Required Tools and Platforms
- SQL
- Python
- Spark
- Scala
- AWS Glue
- Amazon Aurora
- Amazon Athena
- GCP
- Snowflake
- dbt, Airflow, and/or Dagster
- Terraform
- CI/CD tooling
- Git or another version-control platform
- REST APIs
Location, Schedule, and Engagement
- Remote contract opportunity.
- Candidates must be located in LATAM.
- Full-time allocation of approximately 40 hours per week.
- Candidates must be available to work a U.S.-based EST or CST schedule.
- The contract is expected to continue through March 31, 2027.