Job Description

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 idóneo 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.

Qualifications

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

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