GCP Engineer

3 - 6 years

13 - 15 Lacs

Posted:1 day ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

About The Opportunity

We’re a fast-growing

enterprise AI platform provider in the cloud services & software (SaaS) sector

, helping Fortune 500 clients modernize data pipelines, automate knowledge work and unlock new revenue with Generative AI. Backed by a deep bench of AI researchers and cloud architects, we build scalable, production-grade solutions. Join our Pune-based hybrid team to shape the next generation of agentic AI products.Role & Responsibilities
  • Design and implement end-to-end data pipelines on GCP using BigQuery, Cloud Composer, Dataflow, Dataform and Pub/Sub.
  • Develop scalable, secure REST/gRPC APIs that expose analytics and ML features to internal and external consumers.
  • Optimize pipeline resilience & cost through partitioning, autoscaling, job-orchestration, and advanced monitoring (Cloud Monitoring, Stackdriver).
  • Automate DevOps workflows—set up Git-based CI/CD (Cloud Build, Cloud Deploy, Terraform) and enforce IaC best practices.
  • Embed data quality & governance with schema enforcement, versioned data contracts and automated regression testing.
  • Partner cross-functionally with product managers, data scientists and SREs to deliver SLAs and measurable business value.

Skills & Qualifications

Must-Have

  • 3-6 years building large-scale data solutions on Google Cloud Platform (BQ, Composer, Dataflow, Dataform, Pub/Sub).
  • Strong Python development skills plus SQL chops for BigQuery.
  • DevOps expertise: Git, containerization, CI/CD, infra-as-code (Terraform/Cloud Deploy).
  • Proven track record of API development and throughput tuning for high-volume data services.

Preferred

  • Experience integrating or operating Elasticsearch / OpenSearch for log & metric search.
  • Knowledge of streaming frameworks (Kafka, Flink) and advanced performance benchmarking on GCP.
Skills: genrative AI,Python,API Development,GCP,CI,Cd,Git,Data,DevOps,langchain,Kubernetes,elastic search,Data Flow,RAG,LLMs,MLOps,API Platform,Cloud,Advanced,Pipelines

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