#126292 副本 - 数据工程师
Copy of #126292 - Data Engineer
我们正在寻找一名数据工程师，负责设计、构建和维护可扩展的数据流水线、数据集和自动化系统，以支持云成本可见性、归因和性能洞察。
该职位将处理大规模的遥测、使用和财务数据，帮助产品、工程和财务相关方做出知情的成本意识决策。理想的候选人具备扎实的云数据工程经验，熟悉AWS、Snowflake、生产流水线管理、数据质量以及性能和成本优化。
主要职责
* 在云环境中设计、构建和维护可靠的整体ELT和ETL流水线。
* 构建可扩展的数据集，支持云成本可见性、归因、使用分析和性能洞察。
* 设计并实现用于大规模遥测和使用数据的数据模型和摄入框架。
* 开发自动化工具和系统，使产品、工程和财务团队能够进行成本意识决策。
* 优化数据流水线和系统，提高性能、可靠性和成本效率。
* 进行查询调优，改进存储和计算策略。
* 构建和维护与REST API及其他数据源的集成。
* 实施和维护CI/CD流程和基础设施即代码。
* 确保端到端数据工作流中的数据质量、验证、审计和一致性。
* 监控、排查并解决生产流水线故障、数据不一致和性能问题。
* 与工程和财务相关方合作，推动云成本优化和基于使用情况的洞察。
必备技能
* 扎实的数据工程基础，有在云环境中构建和维护整体ELT或ETL流水线的实际经验。
* 熟练掌握SQL和Python。
* 有使用数据工作流和编排工具（如dbt、Airflow或Dagster）的经验。
* 熟悉AWS数据生态系统，包括AWS Glue、Amazon Athena和Amazon Aurora。
* 有Snowflake使用经验。
* 有数据建模经验。
* 有处理大规模数据的经验。
* 有CI/CD和版本控制经验。
* 熟悉使用Terraform进行基础设施即代码实践。
* 有构建或维护REST API集成的经验。
* 有优化数据流水线以提升性能和成本效率的能力。
* 强大的分析和故障排除能力。
* 有数据验证、审计和生产流水线支持经验。
* 有企业级工作经验
查看英文原文
We are seeking a Data Engineer to design, build, and maintain scalable data pipelines, datasets, and automation systems that support cloud cost visibility, attribution, and performance insights.
This role will work with large-scale telemetry, usage, and financial data to help Product, Engineering, and Finance stakeholders make informed, cost-aware decisions. The ideal candidate has strong hands-on experience with cloud data engineering, AWS, Snowflake, production pipeline ownership, data quality, and performance and cost optimization.
Key Responsibilities
* Design, build, and maintain reliable end-to-end ELT and ETL pipelines in cloud environments.
* Build scalable datasets that support cloud cost visibility, attribution, usage analysis, and performance insights.
* Design and implement data models and ingestion frameworks for large-scale telemetry and usage data.
* Develop automation and tooling that enable cost-aware decision-making across Product, Engineering, and Finance teams.
* Optimize data pipelines and systems for performance, reliability, and cost efficiency.
* Perform query tuning and improve storage and compute strategies.
* Build and maintain integrations with REST APIs and other data sources.
* Implement and support CI/CD processes and Infrastructure as Code.
* Ensure data quality, validation, auditability, and consistency across end-to-end data workflows.
* Monitor, troubleshoot, and resolve production pipeline failures, data inconsistencies, and performance issues.
* Partner with Engineering and Finance stakeholders on cloud cost optimization and usage-based insights.
Must-Have Skills
* Strong data engineering foundation with proven experience building and maintaining end-to-end ELT or ETL pipelines in cloud environments.
* Strong SQL and Python skills.
* Experience with data workflow and orchestration tools such as dbt, Airflow, or Dagster.
* Hands-on experience with the AWS data ecosystem, including AWS Glue, Amazon Athena, and Amazon Aurora.
* Experience with Snowflake.
* Strong data modeling experience.
* Experience processing data at scale.
* Experience with CI/CD and version control.
* Hands-on Infrastructure as Code experience using Terraform.
* Experience building or maintaining REST API integrations.
* Demonstrated ability to optimize data pipelines for performance and cost.
* Strong analytical and troubleshooting skills.
* Experience with data validation, auditing, and production pipeline support.
* Enterprise experience strongly preferred.
Nice-to-Have Skills
* Scala experience.
* FinOps Certified Practitioner or FinOps Certified Engineer certification.
* Experience with cloud cost optimization, tagging strategies, or cost-monitoring systems.
* Experience working across both AWS and GCP.
* Experience with Datadog.
* Background in data platform engineering or shared infrastructure engineering.
Required Tools & Platforms
* Python
* SQL
* AWS Glue
* Amazon Athena
* Amazon Aurora
* Snowflake
* dbt, Airflow, or Dagster
* Terraform
* CI/CD tooling
* Git or another version-control platform
* REST APIs
Location, Time & 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.
* Contract expected to continue through March 31, 2027.