Lead Data Engineer

Key Responsibilities

Data Engineering & Pipeline Development
Develop and maintain scalable ETL/ELT pipelines across AWS and GCP environments.
Integrate cloud billing, usage, telemetry, commitment, and operational datasets.
Build data models supporting allocation, forecasting, budgeting, and optimization use cases.
Implement automated data validation and quality controls.

FinOps Data Operations

Support cloud cost allocation and tagging frameworks.
Enable standardized reporting and unit economics calculations.
Maintain data pipelines supporting chargeback/showback processes.
Support automated anomaly detection and alerting capabilities.

Platform Enablement

Build APIs and data services supporting dashboards, analytics, and AskFinOps capabilities.
Implement CI/CD pipelines, automation, and Infrastructure as Code for data platform services.
Optimize pipeline performance, scalability, and reliability.
Support self-service analytics and reporting capabilities.

Collaboration

Partner with FinOps practitioners, analysts, and engineering teams to define data requirements.
Support forecasting and planning initiatives with accurate and timely data.
Participate in platform modernization and automation initiatives.

Required Skills & Experience

5+ years of data engineering experience.
Strong SQL and Python development skills.
Experience with cloud-native data technologies.
Experience building and supporting data pipelines in AWS and/or GCP.
Experience with DevOps practices, CI/CD pipelines, and cloud automation.
Experience with Docker, Kubernetes, and Infrastructure as Code tools.
Understanding of data warehousing and dimensional modeling.
Experience with data orchestration tools and CI/CD pipelines.