Description

You will design and implement secure data pipelines and architectures within the Google Cloud ecosystem, supporting machine learning and analytics projects.

This role is on-site.

Responsibilities

• Design reusable, built-as-code data ingress and egress patterns.
• Build scalable, fault-tolerant data patterns for ML and analytics.
• Construct repeatable batch ETL/ELT pipelines in the cloud.
• Develop data architectures and cloud migration strategies.
• Implement DevOps automation for all stages of data pipeline build and deployment.

Required Skills

• 5+ years of experience in data or cloud engineering.
• Proficiency with Google Cloud SDK and core services: BigQuery, Cloud Pub/Sub, Cloud Storage, and Dataflow.
• Infrastructure-as-code expertise using Terraform, Ansible, and Helm.
• Strong SQL query writing skills for data modeling and analysis.
• Experience with containerization and orchestration using Docker and Kubernetes.
• Hands-on experience with data streaming tools such as Apache Kafka or Oracle GoldenGate.
• Working knowledge of Git and Jenkins for CI/CD and automated workflow orchestration.
• Ability to manage Google Cloud infrastructure including Load Balancers, VM Instances, and Cloud Logging.
• Experience with templating engines like Jinja or Go templates.

Preferred Skills

• Experience with Cognos or Tableau for reporting.

Key Skills

Education

Any Graduate