Gcp Data Engineer

Role & responsibilities

Data Engineer 

• Design, build, and operate scalable data platforms, infrastructure, and self-service capabilities for analytics and operational workloads. 
• Develop and optimize ETL/ELT pipelines using batch, streaming, CDC, and micro-batch ingestion patterns. 
• Manage orchestration platforms (Composer/Airflow), DAG development, scheduling, monitoring, dependency management, and backfills. 
• Implement data security, access controls, monitoring, alerting, and CI/CD best practices. 
• Work with Python, SQL, Terraform, BigQuery, GCS, Pub/Sub, Cloud Run, Fivetran, and dbt. 
• Enable reliable, governed, and high-quality data delivery while collaborating closely with BI, DWH, and Data Science teams. 
• Strong problem-solving, communication, and engineering mindset. 

what are the main 5 must have keywords for the above thing

Preferred candidate profile

• Python
  
• Core programming language for data engineering, ETL pipelines, automation, and data processing.
• SQL
  
• Essential for querying, transforming, and managing large-scale data systems.
• ETL/ELT Pipelines
  
• Covers data ingestion, transformation, CDC, batch, streaming, and micro-batch processing.
• Airflow (Composer)
  
• Key orchestration tool for DAG development, scheduling, monitoring, and workflow management.
• Google Cloud Platform (GCP)
  
• Specifically:
• BigQuery
• Cloud Storage (GCS)
• Pub/Sub
• Cloud Run
• These are critical cloud technologies mentioned in the role.