Description

You will design, build, and optimize scalable data pipelines and architectures on Google Cloud Platform.

This role is remote.

Responsibilities

• Design and develop ETL/ELT pipelines to process large-scale structured and unstructured data.
• Implement data ingestion, transformation, and storage solutions using BigQuery, Cloud Storage, Dataflow, and Pub/Sub.
• Automate infrastructure provisioning and deployment using Terraform, Cloud Composer, or CI/CD tools.
• Optimize and monitor data workflows for performance, scalability, and cost-efficiency.
• Troubleshoot and resolve data pipeline failures and performance bottlenecks.

Required Skills

• 2+ years of experience working with GCP data engineering tools.
• Hands-on experience with Google BigQuery, Dataflow, Pub/Sub, Cloud Functions, and Cloud Storage.
• Strong expertise in SQL, Python, or Java for data processing.
• Knowledge of Apache Beam, Spark, or Kafka for streaming and batch processing.
• Experience with Airflow (Cloud Composer) for orchestration.
• Familiarity with Terraform, Kubernetes, and CI/CD pipelines.
• Understanding of data governance, security, and compliance (GDPR, HIPAA, etc.).
• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.

Preferred Skills

• GCP certifications such as Professional Data Engineer or Associate Cloud Engineer.
• Experience with machine learning pipelines and MLOps in GCP.

Key Skills

Education

Any Graduate