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Popular cloud title, mid-level experience, and broad GCP/Kubernetes/IaC requirements drive high competition.
Strong GCP and data-pipeline specialization increases domain bias while core cloud skills remain somewhat transferable.
Explicit 5–8 years plus mandatory GCP, Dataflow, Terraform, Kubernetes and Python skills enforce strict filtering.
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Develop and maintain scalable, distributed, cloud-native software systems on Google Cloud Platform focusing on performance and reliability.
Collaborate cross-functionally with Cloud, Data, and Platform teams to deliver enterprise-scale solutions and application modernization initiatives.
Improve code quality through unit tests, automation, code reviews, and identify opportunities to optimize system performance and reduce technical debt.
5–8 years of experience in software engineering and application development.
Strong programming expertise in Python and hands-on experience with Google Cloud Platform services including BigQuery, Cloud Run, and Pub/Sub.
Experience with GCP Dataflow / Apache Beam, Terraform or Infrastructure as Code, Kubernetes (GKE), Kafka or similar streaming platforms.
Experience with distributed systems, event-driven architecture, containerization (Docker), microservices design, and CI/CD tools (preferably Harness).
Experienced in designing and building distributed, event-driven data platforms leveraging modern cloud infrastructure and architecture.
Proactive in application modernization, refactoring, and continuous improvement with strong analytical and problem-solving skills.
Comfortable working in Agile/Scrum environments and integrating AI/ML or Generative AI solutions into applications.