DevOps Engineer-II

Role Overview

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.
• Build self-service deployment capabilities and golden-path engineering workflows.

GCP Data Platform Deployments

• Build deployment patterns and automation for Dataproc, BigQuery, Dataform, Cloud Composer, GCS, Dataflow, Bigtable, and Cloud Spanner.
• Enable reliable and repeatable deployment, configuration, and operation of GCP data services.
• Design multi-environment and multi-tenant deployment patterns.

Data Pipeline Delivery

• Design CI/CD workflows for batch data pipelines, streaming workloads, transformation logic, orchestration workflows, and environment-specific releases.
• Improve how data pipelines are built, tested, promoted, and deployed across environments.

Internal Tools and Automation

• Build platform tools, APIs, CLIs, scripts, and reusable libraries using Python and Go.
• Reduce repetitive work and improve developer experience through reusable platform capabilities.
• Apply testing, modular design, versioning, and maintainability practices.

Engineering Partnership

• Work with data, AI, platform, and infrastructure teams to develop scalable platform solutions.
• Help define standards for pipeline design, deployment automation, release management, operational readiness, and CI/CD governance.

Must-Have Qualifications

• Strong experience designing and building CI/CD frameworks for platform or engineering teams.
• Expert-level Google Cloud Platform knowledge and hands-on GCP data-services experience.
• Strong GitLab and GitLab CI/CD pipeline-design experience.
• Strong Python application-development experience and hands-on Go development experience.
• Experience with data-platform, analytics, or AI/ML CI/CD pipelines.
• Ability to build reusable frameworks, deployment templates, automation utilities, and engineering standards.
• Experience working in platform, DevOps, or cloud engineering environments.

Technical Skills

• GCP data services include Dataproc, BigQuery, Dataform, Cloud Composer, GCS, Dataflow, Bigtable, and Spanner.
• Data engineering skills include batch processing, streaming workloads, orchestration frameworks, and data pipeline design.
• Platform and DevOps skills include reusable tooling, automation frameworks, developer enablement, self-service platforms, version control, release workflows, automated validation, and CI/CD governance.