About the Role
You will lead the lifecycle of internal Platform-as-a-Service and Data-as-a-Service products, overseeing highly technical engineering teams and managing significant cloud budgets. You'll ensure enterprise-grade system availability, define and enforce error budgets, and drive production scaling strategies including cloud infrastructure maintenance. You'll own the GCP cloud computing budget, analyze pricing structures, and identify ways to reduce operational costs. Working closely with Data Engineers, you'll prioritize performance tuning of tables and pipelines, ensure the data architecture supports advanced analytics and machine learning, and partner with Legal and Security teams to keep the cloud environment compliant with privacy regulations.
Requirements
- Deep understanding of cloud computing (GCP)
- Experience with infrastructure as code (Terraform)
- Experience with container orchestration (Kubernetes/GKE)
- Knowledge of Site Reliability Engineering principles
- Extensive experience with Data Warehousing, Data Lakes, Business Intelligence (BI)
- Experience with AI/Machine Learning product deployment
- Proven ability to manage large cloud budgets and optimize infrastructure spend within the Google Cloud ecosystem
- Demonstrated experience directly managing technical personnel (engineers, SREs)
- Experience leading cross-functional teams without direct authority
- Ability to translate complex technical infrastructure and data concepts into clear business value for executive stakeholders
Responsibilities
- Define, monitor, and enforce error budgets to ensure 99.99% product availability
- Create and execute production system scaling strategies
- Lead cloud infrastructure operational maintenance such as GKE cluster consolidation
- Own the GCP cloud computing budget
- Analyze pricing structures and identify process flows to reduce operational costs
- Work with Data Engineers to prioritize performance tuning such as partitioning and clustering BigQuery tables
- Optimize ETL/ELT pipelines
- Ensure data architecture supports advanced analytics and Machine Learning models
- Prepare clean, accessible datasets for Data Scientists
- Partner with Legal and Security teams to ensure compliance with privacy regulations (GDPR, CCPA)
- Manage Cloud IAM and data access policies
Benefits
- Equity compensation
- Early exercise for all options, including pre-vested
- Remote-first culture
- Flexible paid time off and year-end break
- Health insurance, dental, and vision coverage for employees and dependents
- 4% matching in 401k / RRSP
- MacBook Pro provided
- One-time home office setup stipend
- Monthly meal stipend
- Monthly social meet-up stipend
- Annual health and wellness stipend
- Annual learning stipend