DevOps Engineer-II

Platform Engineering | Google Cloud | Data & AI Enablement

We are looking for a Senior Developer to help build and evolve the CI/CD frameworks used by our Data and AI Platform teams.

This role is focused on building reusable platform capabilities rather than one-off project-specific implementations. You will work closely with data engineers, AI/ML engineers, and platform teams to design reusable pipelines, automation frameworks, deployment patterns, and self-service engineering capabilities for modern data and AI workloads on Google Cloud Platform.

The right person for this role is hands-on, comfortable writing production-quality code, and has a strong understanding of both cloud services and CI/CD engineering practices. You should be able to take complex platform requirements and turn them into scalable, reusable frameworks that engineering teams can easily adopt.

Key Responsibilities

Build Platform CI/CD Frameworks

• Design and develop reusable GitLab CI/CD frameworks for Data and AI platform teams.
• Create reusable pipeline templates, deployment workflows, validation steps, and automation standards that can be adopted across projects and environments.
• Build self-service deployment capabilities and golden-path engineering workflows for Data & AI teams.
  
  

Enable GCP Data Platform Deployments

• Build deployment patterns and automation for core GCP data services including:
• Dataproc
• BigQuery
• Dataform
• Cloud Composer
• Google Cloud Storage
• Dataflow
• Bigtable
• Cloud Spanner
• Enable teams to deploy, configure, and operate these services through reliable and repeatable CI/CD processes.
• Design frameworks supporting multi-environment and multi-tenant deployment patterns.
  

Support Data Pipeline Delivery

• Design CI/CD workflows for:
• Batch data pipelines
• Streaming workloads
• Transformation logic
• Orchestration workflows
• Environment-specific releases
• Work with engineering teams to improve how data pipelines are built, tested, promoted, and deployed across environments.
  

Develop Internal Tools and Automation

• Build platform tools, APIs, CLIs, scripts, and reusable libraries using Python and Go.
• Focus on reducing repetitive work, improving developer experience, and making platform capabilities easier for teams to adopt.
• Apply software engineering best practices including testing, modular design, versioning, and maintainability to platform tooling and frameworks.
  
  

Partner with Engineering Teams

• Work closely with data, AI, platform, and infrastructure teams to understand engineering challenges and convert them into scalable platform solutions.
• Help define practical standards for:
• Pipeline design
• Deployment automation
• Release management
• Operational readiness
• CI/CD governance
  

Must-Have Qualifications

• Strong experience designing and building CI/CD frameworks for platform or engineering teams.
• Expert-level knowledge of Google Cloud Platform and hands-on experience with GCP data services.
• Deep experience with:
• Dataproc
• BigQuery
• Dataform
• Cloud Composer
• GCS
• Dataflow
• Bigtable
• Spanner
• Strong experience with GitLab and GitLab CI/CD pipeline design.
• Experience designing CI/CD pipelines for data platforms, analytics workloads, or AI/ML platform teams.
• Strong understanding of data pipeline design including:
• Batch processing
• Streaming architectures
• Orchestration
• Transformation workflows
• Environment promotion
• Strong application development experience with Python.
• Hands-on development experience with Go.
• Ability to build reusable frameworks, deployment templates, automation utilities, and engineering standards.
• Experience working with cross-functional engineering teams in platform, DevOps, or cloud engineering environments.
  

Technical Skills

Cloud Platform

• Google Cloud Platform (GCP)
  
  

GCP Data Services

• Dataproc
• BigQuery
• Dataform
• Cloud Composer
• GCS
• Dataflow
• Bigtable
• Spanner
  
  

CI/CD & Automation

• GitLab
• GitLab CI/CD
• Pipeline templates
• Deployment automation
• Environment promotion workflows
  
  

Programming

• Python
• Go
  
  

Data Engineering

• Data pipeline design
• Batch processing
• Streaming workloads
• Orchestration frameworks
  
  

Platform Engineering

• Reusable tooling
• Automation frameworks
• Developer enablement
• Self-service platforms
  
  

DevOps Practices

• Version control
• Release workflows
• Automated validation
• CI/CD governance