Senior Data Engineer: AWS Pipelines & AI-Ready Data

Sirius.; Sydney; Hybrid; AUD 120,000 - 160,000; Full time

Job summary

Sirius Technology is seeking a Senior Data Engineer to design, build and maintain data pipelines on a modern AWS-based data platform. This role focuses on reliability, accessibility and well-structured data to support analytics, API integrations and AI initiatives.

You will design and optimise data models, lead data ingestion from various sources and ensure data quality, governance and performance across the platform. 2 days onsite in Sydney as part of a hybrid work arrangement.

Qualifications

• Extensive experience designing, building and supporting AWS-based data platforms.
• Strong hands-on experience with AWS Glue, PySpark, Lambda, ECS/Fargate, Redshift and S3.
• Advanced SQL and Python development skills and Power BI.
• Experience with dbt, data modelling and ETL/ELT pipeline development.
• Experience building data ingestion, integration and API-based solutions at scale.

Responsibilities

• Design, build and maintain scalable data pipelines and integration solutions across the AWS data platform.
• Develop and support ETL/ELT processes using AWS Glue, PySpark, Lambda and dbt.
• Design and optimise data models within Redshift to support reporting and analytics.
• Lead the ingestion and integration of data from databases, APIs, files and event-driven sources.
• Monitor, troubleshoot and optimise data pipelines to ensure data quality, reliability and performance.
• Implement and maintain metadata, data lineage and governance practices.

Skills

Advanced SQL

Python development

Data modelling

Tools

AWS Glue

PySpark

Lambda

ECS/Fargate

Redshift

S3

dbt

Power BI

Job description

Sirius Technology is seeking a Senior Data Engineer to design, build and maintain data pipelines on a modern AWS-based data platform. This role focuses on reliability, accessibility and well-structured data to support analytics, API integrations and AI initiatives.

You will design and optimise data models, lead data ingestion from various sources and ensure data quality, governance and performance across the platform. 2 days onsite in Sydney as part of a hybrid work arrangement.