Role Overview
Join a high-impact engineering initiative focused on building a Cloud Economics Platform that delivers financial clarity and drives optimization in complex cloud environments. As the Senior Data Engineer (Cloud FinOps), you'll play a central role in shaping how engineering and finance teams understand and act on cloud spending data.
Key Responsibilities
- Design, develop, and maintain robust ELT and ETL pipelines that support accurate cloud cost attribution and financial transparency
- Create and evolve data models that unify infrastructure metrics with financial datasets for performance-aware cost analysis
- Build automated systems to detect cost-saving opportunities, including Reserved Instances and Savings Plans planning
- Deliver reliable, well-documented datasets to cross-functional stakeholders in Product, Engineering, and Finance
- Lead schema design and governance for a scalable Cloud Economics data warehouse, ensuring long-term maintainability
- Conduct thorough data validation and auditing to ensure executive-level reporting accuracy
Required Qualifications
- Proven background in Data Engineering, Cloud Engineering, or FinOps with a focus on cloud cost optimization
- Advanced skills in SQL, Python, and Scala for data transformation and pipeline development
- Hands-on experience with orchestration tools such as dbt, Airflow, or Dagster
- Deep knowledge of cloud platforms—AWS (Glue, Aurora, Athena), GCP, and Snowflake
- Experience with Infrastructure as Code using Terraform and CI/CD workflows
- Strong ability to build and integrate REST APIs for data ingestion
- Proficiency with Datadog for monitoring infrastructure and associated costs
- FinOps Practitioner or FinOps Engineer certification is required
- Experience working in Agile, remote-first teams with fluent English communication
Preferred Qualifications
- Familiarity with discount modeling strategies, including Reserved Instances and Savings Plans
- Experience developing analytics dashboards for predictive cloud cost forecasting
- Background in optimizing queries and performance in large-scale data warehouses
- Understanding of financial modeling concepts, particularly unit economics in cloud environments
Technical Environment
SQL, Python, Scala, dbt, Airflow, Dagster, AWS (Glue, Aurora, Athena), GCP, Snowflake, Terraform, CI/CD, REST APIs, Datadog
Work Model
This role is fully remote with a focus on LATAM regions. Candidates must be able to align with Central Time (CT) within a ±2 hour window to support collaboration across distributed teams.
