GCP Data Engineer — Pipelines, BigQuery & Airflow

Kaizen Global Technologies; Sydney; On-site; AUD 120,000 - 150,000; Full time

Job summary

Kaizen Global Technologies seeks an experienced Data Engineer to design, develop, and manage scalable data pipelines and cloud data platforms using GCP, Python, SQL, and Airflow. Build ETL/ELT workflows, optimize BigQuery workloads, and support dashboards with Looker Studio.

Collaborate with analysts and data scientists to deliver reliable analytics and insights. The role focuses on data modelling, governance, and secure data delivery, with hands-on work across batch and real-time pipelines in a

Qualifications

• Proficient in Python and SQL for data processing.
• Experience with GCP services and Airflow orchestration.
• Strong ETL/ELT pipeline development and data integration.
• Data modelling, transformation and query optimization.
• Focus on data quality, governance and security.
• Experience with batch and real-time data pipelines.
• Nice to have PySpark, Kafka, Docker and CI/CD familiarity.

Responsibilities

• Build and maintain scalable data pipelines on GCP.
• Develop ETL/ELT workflows using Python and SQL.
• Design data models and optimize BigQuery workloads.
• Support dashboards and analytics with Looker Studio.
• Ensure data quality, security, reliability and performance.
• Collaborate with analysts, data scientists and stakeholders.

Skills

Python

SQL

Airflow/Cloud Composer

ETL/ELT pipelines

Data modelling

Data quality

Batch & real-time pipelines

PySpark

Kafka

Docker

CI/CD

Tools

Looker Studio

BigQuery

Job description

Kaizen Global Technologies seeks an experienced Data Engineer to design, develop, and manage scalable data pipelines and cloud data platforms using GCP, Python, SQL, and Airflow. Build ETL/ELT workflows, optimize BigQuery workloads, and support dashboards with Looker Studio.

Collaborate with analysts and data scientists to deliver reliable analytics and insights. The role focuses on data modelling, governance, and secure data delivery, with hands-on work across batch and real-time pipelines in a