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Strong employer brand, popular DevOps role, and broad platform skill requirements increase competition.
High — deep GCP data services, GitLab CI/CD, and platform engineering skills limit cross-industry transferability.
High — requires expert GCP, GitLab CI/CD, and hands-on Python and Go platform engineering experience.
Design and develop reusable GitLab CI/CD frameworks and automation templates for Data and AI platform teams on Google Cloud Platform (GCP).
Build and support deployment patterns and automation workflows for core GCP data services including Dataproc, BigQuery, Dataform, Cloud Composer, GCS, Dataflow, Bigtable, and Spanner.
Collaborate with engineering teams to create self-service deployment capabilities and define standards for pipeline design, deployment automation, and CI/CD governance.
Strong experience designing and building CI/CD frameworks for platform or engineering teams.
Expert-level hands-on knowledge of Google Cloud Platform data services: Dataproc, BigQuery, Dataform, Cloud Composer, GCS, Dataflow, Bigtable, Spanner.
Strong experience with GitLab and GitLab CI/CD pipeline design, including pipeline templates and deployment automation.
Programming experience with Python and hands-on development experience with Go. Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building scalable, reusable CI/CD frameworks and automation specifically for data, analytics, or AI/ML platform workloads on GCP.
Proficient in data pipeline design including batch processing, streaming, orchestration, and environment promotion workflows.
Skilled at partnering with cross-functional teams to define practical engineering standards and improve developer experience through self-service platform tooling.