Sr. Staff Data Engineer

Lead the architecture and implementation of the Unified FinOps Data Platform. Design scalable, cloud-native data solutions that support cost allocation, forecasting, optimization, and reporting. Define data standards, governance frameworks, and engineering best practices. Serve as the technical lead for FinOps data architecture across AWS and GCP environments. Lead DevOps automation, continuous integration and continuous delivery (CI/CD), infrastructure as code, and platform reliability initiatives. Enable artificial intelligence, machine learning, and generative artificial intelligence capabilities through scalable data architectures and governed data products. Support AskFinOps AI use cases, including forecasting, anomaly detection, and intelligent optimization. 8+ years of data engineering experience. 3+ years of experience designing large-scale, cloud-native data platforms. Strong expertise in AWS and/or GCP data ecosystems. Advanced SQL and Python development experience. Experience with modern data platforms such as BigQuery, Snowflake, Databricks, or Redshift. Expertise building extract, transform, load (ETL) and extract, load, transform (ELT) pipelines and data orchestration frameworks. Experience with DevOps practices, including CI/CD, infrastructure as code, and cloud automation. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Experience supporting artificial intelligence, machine learning, or generative artificial intelligence data platforms and solutions. Experience working with financial, billing, usage, or operational analytics datasets. Strong communication and stakeholder management skills. Experience with FinOps, cloud cost management, or cloud financial governance. Experience with Terraform, GitHub Actions, Jenkins, or similar DevOps tools. Experience with Vertex AI or similar artificial intelligence platforms, generative artificial intelligence tools, and AI-enabled analytics platforms. FinOps Certified Practitioner or FinOps Certified Professional certification. Bachelor's degree in Computer Science, Engineering, Analytics, or a related field. Build and maintain enterprise-grade pipelines for cloud billing and usage data. Develop data products that support cost allocation, chargeback and showback, discount and commitment utilization, application and service telemetry, and unit economics. Develop near-real-time ingestion and processing capabilities. Automate reconciliation between cloud provider invoices and financial reporting systems. Enable forecasting and planning models using historical consumption, demand signals, and business growth trends. Support artificial intelligence-enabled insights and decision automation capabilities. Deliver trusted datasets and reporting structures that support Sarbanes-Oxley (SOX) compliance. Establish data quality monitoring, lineage, and observability standards. Collaborate with FinOps, Finance, Product Engineering, Architecture, and Data teams. Mentor engineers and establish engineering standards for the FinOps platform. Drive adoption of data products and self-service reporting capabilities.