Lead GCP Engineer

Job summary

The Lead GCP Engineer designs and operates cloud infrastructure and data engineering solutions across GCP and AWS. Responsibilities include building CI/CD pipelines and batch and streaming data workflows with BigQuery, Cloud Storage, Airflow, Pub/Sub, and Dataflow; managing infrastructure with Terraform and Chef; and deploying Kubernetes applications. The role also supports monitoring, ETL automation, SQL-based data validation, code reviews, and engineer mentoring.

Qualifications

• Bachelor’s degree in Information Technology, Engineering, Analytics, or a related field.
• At least five years of experience in the offered role or a related occupation.
• Hands-on experience with GCP or comparable public cloud platforms and managed services.
• Experience using BigQuery, Cloud Storage, and Google Cloud SDK tools bq and gsutil.
• Experience building data workflows with Airflow, Dataflow, and Pub/Sub.
• Experience developing CI/CD pipelines with GitLab, Jenkins or Drone, and Maven.
• Experience managing infrastructure with Terraform and Chef.
• Object-oriented programming experience in Python or Java, including common design patterns.
• Python and shell scripting experience for automation.
• Working knowledge of SQL for dataset validation.
• Experience working in Agile development environments.

Responsibilities

• Design, develop, and maintain CI/CD pipelines across GCP and AWS.
• Build and support batch and real-time data ingestion pipelines and streaming analytics solutions.
• Develop data processing workflows using BigQuery, Cloud Storage, and Google Cloud SDK tools bq and gsutil.
• Create and manage Airflow DAGs to schedule and monitor pipeline execution.
• Implement event-driven and streaming integrations using Pub/Sub and Dataflow.
• Provision and manage cloud infrastructure with Terraform and Chef.
• Deploy and support containerized applications on GKE and AWS-managed Kubernetes services.
• Maintain monitoring, alerting, and health checks for cloud infrastructure and data pipelines.
• Automate ETL workflows using cloud tools, Terraform, Python, and shell scripts.
• Translate requirements into scalable cloud and data engineering solutions with cross-functional teams.
• Review code and mentor engineers to improve quality and support DevOps deployments.
• Write and validate SQL queries to verify datasets and troubleshoot data processing issues.

Skills

Degrees

Languages

Work schedule

Relocation