Data Engineer

Team: IT

Location: Brazil

Commitment: Full-time

Workplace Type: remote

Accountabilities

• Design, build, and maintain scalable data pipelines and automation systems supporting cloud economics and cost intelligence.
• Develop robust datasets and data models that enable cloud cost visibility, attribution, usage analysis, and performance insights.
• Design and implement ingestion frameworks capable of processing large-scale telemetry and cloud usage data.
• Build data tooling that enables Product, Engineering, and Finance stakeholders to make informed, cost-aware decisions.
• Optimize data systems for performance, reliability, scalability, and cost efficiency through query tuning, storage strategies, and compute optimization.
• Partner closely with Engineering and Finance teams to support cloud cost optimization initiatives and usage-based analysis.
• Establish and maintain strong data quality, validation, auditability, and troubleshooting practices across end-to-end workflows.
• Contribute to reliable production data operations through effective monitoring, testing, version control, and infrastructure practices.
• Identify opportunities to automate recurring processes and improve the efficiency of data engineering workflows.

Requirements

• Strong foundation in data engineering, with proven experience designing and maintaining end-to-end ETL/ELT pipelines in cloud environments.
• Strong proficiency in SQL and Python; experience with Scala is a plus.
• Hands-on experience with orchestration and transformation tools such as dbt, Airflow, or Dagster.
• Practical experience with the AWS data ecosystem, including AWS Glue, Amazon Athena, and Amazon Aurora.
• Experience working with Snowflake or another modern cloud data warehouse.
• Strong data modeling and large-scale data processing capabilities.
• Experience with CI/CD practices, GitHub or similar version-control platforms, and Infrastructure as Code using tools such as Terraform.
• Experience integrating REST APIs into data pipelines and engineering workflows.
• Demonstrated ability to optimize pipelines and data systems for both performance and cost.
• Strong analytical and troubleshooting skills, including experience with data validation, auditing, and resolving production pipeline issues.
• FinOps Foundation certification at Practitioner or Engineer level is a plus.
• Experience with cloud cost optimization, tagging strategies, or cloud cost monitoring is advantageous.
• Experience working across both AWS and GCP is a plus.
• Familiarity with Datadog or comparable monitoring and observability platforms is beneficial.
• Background in data platform engineering or shared infrastructure engineering is an advantage.
• Strong communication and collaboration skills, with the ability to work effectively with technical and business stakeholders.
• Availability to collaborate with teams working primarily across U.S. Eastern or Central time zones.

Benefits

• Competitive long-term total compensation package, including salary and performance-based bonus.
• Remote-first working environment with a strong emphasis on flexibility.
• Opportunities to work alongside experienced engineers and technology leaders.
• Access to technical and non-technical training and professional development programs.
• Opportunities for continuous learning and career growth.
• Global exposure through collaboration with international teams and clients.
• Opportunities to attend virtual and in-person international technology conferences.
• Collaborative environment focused on innovation, knowledge sharing, and technical excellence.