Staff Software Engineer - Cloud Platform

• Design and implement cloud infrastructure using IaC – Terraform etc.
• Automate provisioning and management of Dataproc clusters, Dataflow jobs, and other GCP resources
• Integrate tools like GitLab CI/CD, or Cloud Build for automated testing and deployment.
• Deploy and manage real-time and batch data pipelines using Dataflow or DataStream.
• Ensure seamless integration of data pipelines with other GCP services like Big Query, Cloud Storage, and Kafka or Pub/Sub.
• Monitor performance, reliability, and cost of Dataproc clusters, Dataflow jobs, and streaming applications.
• Optimize cloud infrastructure and data pipelines for performance, scalability, and cost-efficiency.
• Implement security best practices for GCP resources, including IAM policies, encryption, and network security.
• Ensure Observability is an integral part of the infrastructure platforms and provides adequate visibility about their health, utilization, and cost.
• Collaborate extensively with cross functional teams to understand their requirements; educate them through documentation/trainings and improve the adoption of the platforms/tools. 

• 10+ years of overall experience in DevOps -cloud engineering, or data engineering.
• 5+ years of experience in DevOps, cloud engineering, or data engineering.
• Proficiency in Google Cloud Platform (GCP) services, including Dataflow, DataStream, Dataproc, Big Query, and Cloud Storage.
• Expertise in Infrastructure as Code (IaC) tools like Terraform or Cloud Deployment Manager.
• Strong experience with Looker, Tableau, or ThoughtSpot administration
• Knowledge of real-time data streaming technologies (e.g., Apache Kafka, Pub/Sub).
• Familiarity with data orchestration tools like Apache Airflow or Cloud Composer.
• Strong proficiency in SQL query optimization
• Experience with CI/CD tools like Jenkins, GitLab CI/CD, or Cloud Build.
• Knowledge of containerization and orchestration tools like Docker and Kubernetes.
• Strong scripting skills for automation (e.g., Bash, Python).
• Experience with monitoring tools like Cloud Monitoring, Prometheus, and Grafana.
• Familiarity with logging tools like Cloud Logging or ELK Stack.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.
• Ability to work in a fast-paced, agile environment.

Compensation will vary based on geographical location (see below) within the United States. Individual pay is determined by the candidate's location of residence and multiple factors, including job-related skills, experience, and education.

For more information on our benefits click here.

There are different ranges applied to specific locations. The average base pay range (or OTE range for sales) in the U.S. for the position is listed below.

San Francisco Bay Area Only:

All Other Locations: