Top Data Engineer Jobs in Melbourne

As a Data Engineer II, you will design and build scalable data pipelines, transform raw data, monitor data systems, and collaborate with teams to meet analytics needs. Responsibilities include data validation, compliance, performance optimization, and creating documentation for workflows.

Data Engineers at Lexer build systems to process and analyze large volumes of customer data, collaborating with teams to keep data flowing and make it available for analysis. They engage in software engineering tasks, system design, and mentorship, while advocating for the product and supporting the team with technical expertise.

As a Principal Data Engineer, you'll perform hands-on data engineering across various projects, provide guidance on data strategy and architecture, and support pre-sales activities. You'll engage with clients, particularly C-level executives, to develop innovative data-driven solutions and improve operations through effective data governance.

InfoCentric is hiring an AWS Data Engineer with a minimum of 3 years proven experience in data engineering, proficiency in Data Warehousing, AWS Cloud experience, and strong skills in Python and SQL. The ideal candidate will have experience with Snowflake and DBT.

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.

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 Senior Data Engineer role involves building, optimizing, and maintaining data applications, systems, and services. You will deploy data pipelines and processes, work in the cloud with various data services, and contribute to a DataOps culture while collaborating with skilled consultants on complex data challenges.