This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer, Cloud Cost & Usage Platform based in Brazil.
This role offers the opportunity to build scalable data infrastructure supporting cloud cost visibility and FinOps initiatives.
You will engineer high-volume pipelines and datasets that transform infrastructure telemetry and usage data into actionable insights.
Your work will help Product, Engineering, and Finance teams understand, attribute, and optimize cloud spending.
You will own critical data workflows from ingestion and modeling through validation, monitoring, and production reliability.
The environment is highly collaborative, distributed, and technically focused, with close interaction across engineering and finance functions.
You will work extensively with modern cloud data technologies including Snowflake, AWS, Python, SQL, dbt, Airflow, Dagster, and Terraform.
This is a high-impact opportunity for a senior engineer who enjoys solving complex data challenges while improving cloud efficiency at scale.
Accountabilities
- Design, build, maintain, and optimize scalable data pipelines, automation systems, and datasets supporting cloud cost visibility, attribution, and usage insights.
- Develop robust data models and ingestion frameworks capable of processing large volumes of telemetry, infrastructure, and usage data.
- Build specialized tooling that enables Product, Engineering, and Finance stakeholders to make informed, cost-aware decisions.
- Optimize data platforms for performance, reliability, scalability, and cost efficiency through query tuning, storage optimization, and compute improvements.
- Partner closely with Engineering and Finance teams to support cloud cost optimization initiatives and develop meaningful usage-based insights.
- Establish and maintain strong data quality, validation, auditing, monitoring, and troubleshooting practices across production workflows.
- Implement and maintain ELT/ETL processes and orchestration workflows using appropriate modern data engineering tools.
- Contribute to CI/CD, Infrastructure as Code, version control, and REST API integrations supporting reliable data platform operations.
- Collaborate effectively with distributed teams across LATAM and the United States, maintaining several hours of overlap with Central Time (CT).
Requirements
- Strong professional experience in Data Engineering, with a proven track record of building and maintaining end-to-end ELT/ETL pipelines in cloud environments.
- Advanced SQL and Python skills, with hands-on experience working with Snowflake.
- Direct experience with modern data orchestration tools such as dbt, Airflow, or Dagster.
- Strong knowledge of the AWS data ecosystem, particularly AWS Glue, Amazon Athena, and Amazon Aurora.
- Solid experience with CI/CD, Git or other version-control systems, Terraform/IaC, and REST API integrations.
- Extensive knowledge of data modeling and large-scale data processing architectures.
- Fluent English, with the ability to conduct interviews, documentation, meetings, and daily technical communication in English.
- Strong analytical and problem-solving skills, with an ability to balance scalability, reliability, performance, and cost.
- Effective communication and collaboration skills for working with technical and business stakeholders in a distributed environment.
- Experience with cloud cost optimization, FinOps practices, tagging strategies, or cost monitoring is highly desirable.
- Familiarity with GCP, Datadog, or multi-cloud environments is a plus.
- Experience with Scala and/or a FinOps Foundation Practitioner or Engineer certification is also considered an advantage.
Benefits
- Full-time remote position for professionals based in LATAM, including Brazil.
- Remote-first work environment with distributed international teams.
- Opportunity to work on a high-impact cloud economics and FinOps initiative.
- Direct exposure to large-scale cloud telemetry, usage analytics, and cost optimization challenges.
- Collaboration with Product, Engineering, and Finance stakeholders.
- Work with modern data engineering and cloud technologies across AWS and Snowflake.
- Long-term opportunity within an international technical environment.
- Flexible collaboration model aligned with Central Time (CT ±2), with several hours of overlap with US-based teams.
- Daily communication, documentation, and collaboration in English.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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