Job Summary
We are seeking a GCP DevOps & Data Engineer Consultant to design, implement, and support enterprise cloud infrastructure and data engineering solutions on Google Cloud Platform. The role will focus on cloud-native data pipelines, infrastructure automation, CI/CD, containerized workloads, cloud data platforms, integrations, security, monitoring, and cloud modernization initiatives. The position will collaborate with technical teams and client stakeholders to deliver secure, scalable, and high-performing cloud solutions.

Key Responsibilities
• 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 GCP services.
• Design, deploy, and automate scalable cloud infrastructure using Terraform and Infrastructure as Code best practices.
• Develop and maintain enterprise CI/CD pipelines using GitOps methodologies, Azure DevOps, and modern DevOps practices.
• Manage artifact repositories, release pipelines, and package lifecycles 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 improvement.
• 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.

Required Qualifications
• Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent work experience.
• 3–5 years of experience in DevOps Engineering, Cloud Engineering, Data Engineering, or Infrastructure Automation.
• 2+ years of hands-on experience implementing solutions on Google Cloud Platform, including GKE, Cloud Run, BigQuery, AlloyDB, Cloud Storage, and serverless technologies.
• 2+ years of experience building and supporting enterprise data pipelines using Databricks.
• 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.
• Ability to travel up to 20–30% based on client engagements and project delivery requirements.

Preferred Qualifications
• Experience supporting Salesforce Agentforce or AI-enabled cloud platforms.
• Experience with Generative AI workloads and the 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.
• Experience serving as a technical lead or supporting project delivery.