Senior DevOps Engineer (UDP)

Role Overview

Platform CI/CD Frameworks

• Design and develop reusable GitLab CI/CD frameworks for data and AI platform teams.
• Create 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, Google Cloud Storage, Dataflow, Bigtable, and Cloud Spanner.
• Enable reliable and repeatable deployment, configuration, and operation of GCP data services.
• Design frameworks for 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 to platform tooling.

Engineering Partnership

• Work with data, AI, platform, and infrastructure teams to turn engineering challenges into 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 experience with GCP data services.
• Deep experience with Dataproc, BigQuery, Dataform, Cloud Composer, GCS, Dataflow, Bigtable, and 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 batch processing, streaming architectures, orchestration, transformation workflows, and environment promotion.
• Strong application development experience with Python and hands-on development experience with Go.
• Ability to build reusable frameworks, deployment templates, automation utilities, and engineering standards.
• Experience working with cross-functional teams in platform, DevOps, or cloud engineering environments.

Technical Skills

• Cloud platform: Google Cloud Platform.
• GCP data services: Dataproc, BigQuery, Dataform, Cloud Composer, GCS, Dataflow, Bigtable, and Spanner.
• CI/CD and automation: GitLab, GitLab CI/CD, pipeline templates, deployment automation, and environment promotion workflows.
• Programming: Python and Go.
• Data engineering: data pipeline design, batch processing, streaming workloads, and orchestration frameworks.
• Platform engineering: reusable tooling, automation frameworks, developer enablement, and self-service platforms.
• DevOps practices: version control, release workflows, automated validation, and CI/CD governance.