Google Cloud Platform DevOps & Data Engineer Consultant

• Design, implement, and support enterprise cloud infrastructure and data engineering solutions on Google Cloud Platform.
• Develop and optimize cloud-native data ingestion, transformation, and processing pipelines using Databricks and Google Cloud Platform services.
• Design, deploy, and automate scalable cloud infrastructure using Terraform following Infrastructure as Code best practices.
• Develop and maintain enterprise CI/CD pipelines utilizing GitOps methodologies, Azure DevOps, and modern DevOps practices.
• Manage artifact repositories, release pipelines, and package lifecycle using JFrog Artifactory.
• Deploy, manage, and optimize containerized workloads running on Google Kubernetes Engine (GKE) and Cloud Run.
• Develop scalable integrations using Google Pub/Sub, Kafka, REST APIs, and event-driven architecture patterns.
• Administer and optimize Google Cloud data platforms including BigQuery, AlloyDB, Cloud Storage, and Spanner.
• Monitor cloud infrastructure, deployment pipelines, application performance, and operational health while driving continuous improvements.
• Implement Google Cloud security controls including IAM, encryption, network security, compliance, and governance standards.
• Collaborate with solution architects, developers, data engineers, and client stakeholders to deliver secure, scalable, and high-performing cloud platforms.
• Participate in architecture reviews, technical assessments, migration planning, and cloud modernization initiatives while providing implementation guidance and best practices.
• Support pre-sales activities by contributing to solution design, effort estimation, technical documentation, and client presentations when required.

• Minimum 3 5 years of experience in DevOps Engineering, Cloud Engineering, Data Engineering, or Infrastructure Automation.
• Minimum 2+ years of hands-on experience implementing solutions on Google Cloud Platform, including GKE, Cloud Run, BigQuery, AlloyDB, Cloud Storage, and serverless technologies.
• Minimum 2 years of experience building and supporting enterprise data pipelines using Databricks.
• Minimum 2 years of experience implementing Infrastructure as Code using Terraform.
• Experience developing and maintaining CI/CD pipelines using GitOps methodologies and Azure DevOps.
• Experience managing build artifacts and repositories using JFrog Artifactory.
• Experience working with Pub/Sub, Kafka, REST APIs, and event-driven integration architectures.
• Strong understanding of Google Cloud IAM, encryption, networking, monitoring, and cloud security best practices.
• Strong analytical, troubleshooting, automation, and problem-solving skills.
• Excellent verbal and written communication skills with the ability to work effectively in cross-functional and client-facing environments.

Degree: Bachelor’s degree in computer science, Engineering, Information Technology, or equivalent work experience. Nice to Have:

• Experience supporting Salesforce Agentforce or AI-enabled cloud platforms.
• Experience with Generative AI workloads and Google Gemini ecosystem.
• Experience with Kubernetes administration and platform engineering.
• Experience with monitoring tools such as Cloud Monitoring, Prometheus, or Grafana.
• Experience working in consulting or professional services organizations.
• Technical lead or project delivery experience.

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