Description

You will design, build, and optimize data pipelines and analytics solutions on Google Cloud Platform. You own the end-to-end data engineering lifecycle, from ingestion to warehousing, ensuring scalability, security, and cost efficiency.

This role is on-site.

Responsibilities

• Develop ETL/ELT processes to extract, transform, and load data into BigQuery and other target systems.
• Design and implement scalable data pipelines using Dataflow, Pub/Sub, and Cloud Run with Python and Linux scripting.
• Build and maintain data models, data warehouses, and data lakes for analytics and reporting.
• Optimize BigQuery queries, manage partitioning and clustering, and handle cost optimization.
• Automate deployments and manage infrastructure using Terraform, Cloud Build, and CI/CD pipelines.

Required Skills

• 8+ years of experience in data engineering, ETL/ELT, and data architecture.
• Strong expertise in Google Cloud Platform services: BigQuery, Cloud Storage, Cloud Run, Dataflow, Cloud SQL, AlloyDB, Cloud Balancer, Pub/Sub, IAM, Logging, and Monitoring.
• Proficiency in SQL, Python, and Linux scripting.
• Experience with data modeling (star/snowflake) and data warehousing concepts.
• Familiarity with CI/CD, Git, and Infrastructure as Code (Terraform).
• Background with ETL tools such as Datastage, Informatica, or SSIS.

Preferred Skills

• Google Cloud Platform Professional Data Engineer or Cloud Architect certification.

Key Skills

Education

Any Graduate