About The Opportunity

A fast-scaling technology solutions provider in the Cloud Data Engineering and AI/ML enablement space, we architect and deploy scalable, secure, and cost-optimized data platforms on Google Cloud Platform (GCP) for enterprise clients across BFSI, Healthcare, and Retail. Our data engineering teams build end-to-end data pipelines, modern data lakes, and real-time analytics solutions that power business intelligence, ML models, and generative AI applications—delivering measurable ROI through clean, governed, and production-ready data infrastructure.

Role & Responsibilities

Design, build, and optimize scalable data pipelines on GCP using Dataflow, Pub/Sub, BigQuery, and Cloud Storage.
Develop and maintain ETL/ELT workflows using Python, SQL, and GCP-native tools for batch and streaming data ingestion.
Implement data governance, lineage, and quality monitoring using Dataplex, Data Catalog, and custom validation frameworks.
Collaborate with Data Scientists and ML Engineers to productionize feature stores and model training pipelines using Vertex AI and BigQuery ML.
Automate deployment and infrastructure provisioning via Terraform, Cloud Build, and CI/CD pipelines.
Monitor system performance, cost, and scalability—optimizing queries, partitioning strategies, and resource allocation across GCP services.

Skills & Qualifications

Must-Have
BigQuery
Dataflow
Pub/Sub
Terraform
Python
SQL
Cloud Storage
Vertex AI
Preferred
Dataplex
Looker
Apache Beam

Benefits & Culture Highlights

Work on enterprise-grade GCP projects with global clients across high-impact industries.
Access to GCP certification sponsorships and hands-on upskilling in modern data stack technologies.
On-site collaborative environment with agile teams, innovation sprints, and direct mentorship from cloud architects.

Skills: cloud,gcp,ml,infrastructure

GCP Data Engineer