Description

Design and implement scalable data and application solutions on Google Cloud Platform, defining technology stacks and trade-offs for cost, performance, and availability.

This role is hybrid.

Responsibilities

• Architect GCP-native solutions using GCS, GKE, PubSub, Composer, BigQuery, Bigtable, CloudSQL, IAM, and Secret Manager.
• Define High-Level and Low-Level design diagrams for the entire solution stack, selecting appropriate technologies and evaluating trade-offs.
• Develop infrastructure as code using Terraform Cloud/Enterprise and manage CI/CD pipelines with GitHub Workflows.
• Build and maintain Python-based data pipelines using Airflow DAGs in Composer and optimize BigQuery performance via partitioning, clustering, and UDFs.
• Implement secure API development using FastAPI or Flask, integrating GCP client libraries and ensuring observability with OpenTelemetry.

Required Skills

• GCP Professional Cloud Architect certification plus one additional professional certification (Data Engineer or Cloud Developer).
• 10+ years of experience in cloud architecture and full-stack development.
• Proficient in Python programming, including PEP8 conventions, pytest unit testing, and GCP client libraries.
• Deep expertise in BigQuery (SQL, joins, IAM, query federation) and data engineering tools like Dataproc.
• Experience with containerization (Docker), microservices, and API lifecycle management (authentication, authorization, middleware).
• Strong understanding of GCP networking, IAM, and security best practices.
• Ability to design robust systems addressing high availability and disaster recovery.

Preferred Skills

• Hands-on experience with GenAI on GCP Vertex AI, Gemini, and the LangChain framework.
• Experience in the Banking or financial domain.

Key Skills

Education

Not specified