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Mid-level data engineer in Pune with broad GCP and pipeline skills increases applicant density and competition.
Core GCP data engineering skills transfer easily across industries; sector experience is optional.
Explicit 3+ years requirement plus mandatory GCP, pipeline, and Terraform skills narrows candidate pool.
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Design, build, and maintain reliable, scalable data integration pipelines and workflows across Google Cloud Platform services including Vertex AI for the AI Search Platform.
Develop and maintain secure, performant APIs exposing data integration and AI capabilities to internal and external consumers, including managing authentication and access control.
Continuously monitor, improve, and document data pipeline reliability, latency, cost efficiency, and compliance including API and IAM policies.
3+ years of professional experience in data engineering, cloud integrations, or backend development with production data pipelines on GCP.
Strong proficiency in Python and SQL; production experience with GCP services: Cloud Run, Pub/Sub, Cloud Storage, Cloud Spanner, Vertex AI.
Experience with event-driven architectures, ETL/ELT cloud data workflows, containerization (Docker), Git, CI/CD, and Infrastructure-as-Code tooling such as Terraform.
Working knowledge of IAM, data governance, and access management principles.
Work Experience Required: 3+ years in relevant data engineering or cloud integration roles.
Experienced in developing event-driven, cloud-native data pipelines specifically on Google Cloud Platform with practical production deployment and operational ownership.
Comfortable working across DevOps, Network, and Platform engineering teams to deliver integrated, secure, and compliant data solutions in a SaaS environment.
Prefers handling incomplete requirements and ambiguity in upstream specs, showing strong ownership of pipeline monitoring, troubleshooting, and continuous improvement.