Senior AWS Data Engineer - Build Scalable Data Pipelines

Zone IT Solutions Pty Ltd; Sydney; Sur place; AUD 140 000 - 190 000; Plein temps

Résumé du poste

Zone IT Solutions Pty Ltd is seeking an experienced AWS Data Engineer to design, build, and maintain scalable data pipelines on AWS for enterprise analytics. You will work with SQL, Python, and AWS data services to deliver robust data solutions.

You will collaborate with data analysts and engineers to model datasets, implement data quality checks, and support production deployments. This role requires 8–10 years of data engineering expertise and a strong passion for data-driven decision making.

Qualifications

• 8–10 years’ experience as a Data Engineer.
• Advanced SQL skills and data modelling knowledge.
• Hands-on AWS experience with services like S3, Redshift, Athena, EMR.
• Proficient in Python and PySpark for data transformations.
• Experience delivering data pipelines in large enterprise environments.
• Familiarity with Airflow or similar orchestration tools.

Responsabilités

• Design, develop, and maintain end-to-end data pipelines on AWS.
• Build ETL/ELT workflows using AWS services and dbt.
• Ingest data from diverse sources into lake/warehouse layers.
• Develop transformation logic with SQL and Python/PySpark.
• Implement data quality checks, monitoring, and alerts.
• Collaborate with analysts/data scientists for analytics-ready datasets.
• Contribute to DataOps/DevOps practices and documentation.
• Optimize pipeline performance and support production deployments.

Connaissances

Advanced SQL

Python

PySpark

AWS data services

ETL/ELT design

Airflow

Outils

Airflow

dbt

Teradata

Siebel CRM

Description du poste

Zone IT Solutions Pty Ltd is seeking an experienced AWS Data Engineer to design, build, and maintain scalable data pipelines on AWS for enterprise analytics. You will work with SQL, Python, and AWS data services to deliver robust data solutions.

You will collaborate with data analysts and engineers to model datasets, implement data quality checks, and support production deployments. This role requires 8–10 years of data engineering expertise and a strong passion for data-driven decision making.