AWS Data Engineer - End-to-End Data Pipelines

CareCone Group; Sydney; On-site; AUD 110,000 - 160,000; Full time

Job summary

CareCone Group is seeking an AWS Data Engineer to design, build, and maintain end-to-end data pipelines on the AWS Data Platform from Sydney. You will implement robust ETL/ELT workflows using AWS Glue, S3, Redshift, Athena, EMR, and dbt, and manage data ingestion from diverse sources into lake/warehouse layers.

You will develop transformation logic with SQL and Python/PySpark, implement data quality checks, and collaborate with data analysts and scientists to model datasets for analytics and ML.

Qualifications

• Advanced SQL skills required.
• Hands-on experience with Teradata and Siebel CRM data.
• Experience delivering pipelines in large enterprise platforms.
• Strong AWS experience: S3, Glue, Redshift, Athena, EMR, dbt.
• Python and PySpark for transformations.
• Experience with Airflow for orchestration.
• Understanding of data warehousing concepts.
• Experience with monitoring and operational support.

Responsibilities

• Design, develop, and maintain end-to-end data pipelines on AWS.
• Build ETL/ELT workflows using AWS services and dbt.
• Ingest data from databases, APIs, files, and streams into lake/warehouse layers.
• Develop transformation logic with SQL, Python, PySpark.
• Implement data quality checks, monitoring, and alerts.
• Collaborate with analysts/scientists on data models for analytics/ML.
• Contribute to DataOps/DevOps: versioning, CI/CD, testing, release, support.
• Document data flows, mappings, jobs, and runbooks.
• Optimize pipeline performance and manage orchestration/scheduling.
• Support production deployments and operations.

Skills

Advanced SQL

AWS data services

Python/PySpark

Airflow

dbt

Teradata

Siebel CRM data

Data warehousing concepts

DataOps/DevOps

Communication with stakeholders

Tools

dbt

Airflow

ETL/ELT pipelines

Job description

CareCone Group is seeking an AWS Data Engineer to design, build, and maintain end-to-end data pipelines on the AWS Data Platform from Sydney. You will implement robust ETL/ELT workflows using AWS Glue, S3, Redshift, Athena, EMR, and dbt, and manage data ingestion from diverse sources into lake/warehouse layers.

You will develop transformation logic with SQL and Python/PySpark, implement data quality checks, and collaborate with data analysts and scientists to model datasets for analytics and ML.