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As a Data Engineer, you will support and improve the existing Python-based reporting pipeline, integrating data from multiple sources. Responsibilities include maintaining SLAs, troubleshooting issues, redesigning processes for stability, and working independently to enhance data pipeline efficiency.

The AWS Data Engineer is responsible for designing and maintaining data pipelines within AWS and Snowflake, ensuring data quality and performance. They collaborate with stakeholders to deliver data-driven solutions, manage data warehouses, and oversee data governance practices.

The Data Architect will design and optimize scalable data architectures on AWS, build ETL pipelines using AWS Glue and other tools, manage data governance and security, and oversee database management. The role requires collaboration with cross-functional teams to meet data needs and involves documentation of data architectures and processes.

The AWS Data Engineer will work in a Data Analytics and Engineering role, focusing on data processing, optimization, and building scalable data solutions. Responsibilities include utilizing AWS tools and collaborating with stakeholders to deliver quality data initiatives.

The Data Engineer will develop and maintain data architectures including databases and large-scale processing systems. Responsibilities include optimizing SQL queries, collaborating with stakeholders to understand requirements, and integrating data from various sources.

As an Azure Cloud Engineer, you will design and implement cloud platforms for various Australian brands, focusing on modernizing data ecosystems. You will work with data architecture and modeling, and collaborate with the Head of Architecture on delivering solutions using Azure services and technologies. Responsibilities include developing applications with Python/pySpark and utilizing CI/CD and source control tools.