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 Enable standardized reporting and unit economics calculations. Support automated anomaly detection and alerting capabilities. Build APIs and data services supporting dashboards, analytics, and AskFinOps capabilities. Implement CI/CD pipelines, automation, and Infrastructure as Code for data platform services. Support self-service analytics and reporting capabilities. Support forecasting and planning initiatives with accurate and timely data. Participate in platform modernization and automation initiatives. 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. Knowledge of cloud cost management and FinOps principles. Experience with BigQuery, Snowflake, Databricks, Airflow, or similar technologies. Experience with GitHub Actions, Jenkins, Terraform, or similar DevOps technologies. Experience with Generative AI tools and AI-enabled analytics platforms. Bachelor's degree in Computer Science, Engineering, Analytics, or related discipline.
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