Lead GCP Engineer

GameStop•Grapevine, TX

2d•Onsite

About The Position

GameStop is seeking a Lead GCP Engineer to design, develop, and maintain automated CI/CD pipelines, data ingestion pipelines, and streaming analytics solutions. This role involves building and operating data processing workflows using GCP services, managing data orchestration with Airflow, and implementing event-driven integrations. The Lead GCP Engineer will also provision and manage cloud infrastructure using Infrastructure as Code, deploy container-based applications on Kubernetes, and implement monitoring and alerting. Additionally, this position involves enhancing ETL automation, collaborating with teams to create scalable solutions, conducting code reviews, mentoring engineers, and writing SQL queries.

Requirements

Bachelor’s degree in Information Technology, Engineering (Any), Analytics, or a related field of study
Five (5) years of experience in the job offered or related occupation
Demonstrated experience with Google Cloud Platform (GCP) or comparable public cloud platforms, including hands-on use of managed cloud services
Demonstrated experience using BigQuery, Cloud Storage, and the Google Cloud SDK, including tools (bq and gsutil)
Demonstrated experience building and maintaining data workflows using Apache Airflow (DAGs), cloud data processing services (Dataflow) and messaging/streaming services (Pub/Sub)
Demonstrated experience developing and maintaining CI/CD pipelines using tools (GitLab, Jenkins/Drone), and build tools (Maven)
Demonstrated experience provisioning and managing cloud infrastructure using Infrastructure as Code (IaC) tools (Terraform) and configuration management tools (Chef)
Demonstrated experience with object-oriented programming using Python and/or Java, including applying common design patterns
Demonstrated experience with shell scripting and Python for automation
Working knowledge of SQL, including the ability to write queries to validate and verify datasets
Working in environments that follow Agile development practices

Responsibilities

Design, develop, and maintain automated CI/CD pipelines using cloud-hosted services on GCP and AWS.
Develop and support batch and real-time data ingestion pipelines and streaming analytics solutions using standardized architectures.
Build and operate data processing workflows using GCP services including BigQuery, Cloud Storage, and the Google Cloud SDK (bq, gsutil).
Develop and manage data orchestration workflows using Airflow (DAGs) to schedule and monitor pipeline execution.
Implement event-driven and streaming integrations using services such as Pub/Sub and Dataflow, as required by solution design.
Provision and manage cloud infrastructure using Infrastructure as Code (IaC) tools such as Terraform and Chef, while maintaining configuration standards.
Deploy, operate, and support container-based applications using Kubernetes platforms including Google Kubernetes Engine (GKE) and AWS-managed Kubernetes services, as applicable.
Implement and maintain monitoring, alerting, and performance health checks to ensure the availability and reliability of cloud infrastructure and data pipelines.
Develop and enhance ETL automation using cloud-centric tools, Terraform automation, and scripting with Python and shell scripting.
Collaborate with leadership, architects, and development teams to translate requirements into scalable cloud and data engineering solutions.
Conduct code reviews and mentor engineers to improve code quality and support DevOps deployment processes.
Write and validate SQL queries to verify datasets and troubleshoot data processing issues.