#126292 - Data Engineer
Summary
Design, build, and maintain scalable ELT/ETL pipelines, datasets, and automation supporting cloud cost visibility, attribution, and performance insights from large-scale telemetry, usage, and financial data. Core stack: Python, SQL, AWS (Glue, Athena, Aurora), Snowflake, dbt/Airflow/Dagster, and Terraform.
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.
