Top Data Engineer Jobs in Melbourne

The Senior Engineer role focuses on database consulting, support, and infrastructure modernization, guiding teams on database design, migration, and performance optimizations.

The role involves designing and optimizing data pipelines for migrating data from Salesforce to Snowflake, ensuring data quality and efficiency.

As a Data Engineer, you will design, build, and maintain data platforms using Azure Data Factory, dbt, and Snowflake to ensure data quality and support integration.

Lead the design and optimization of the enterprise data platform, overseeing development, ensuring scalability and compliance, mentoring junior engineers, and enhancing capabilities with emerging technologies.

As a Data Engineer, you'll build scalable data pipelines, collaborate with marketing teams, ensure data quality, and optimize existing infrastructure to support analytics.

Design, build and operationalise a governed enterprise data foundation and reusable data products to support analytics, AI and downstream applications. Ensure data quality, lineage, auditability and regulatory compliance while collaborating with engineers, architects, data owners and stakeholders.

Seeking Data Engineers to modernize data platforms, optimize existing Snowflake datasets, and contribute to solution design and technical decisions in a consulting environment.

Design, build and optimise cloud-first data pipelines and data models using Snowflake, dbt and Azure tools. Mentor other engineers, implement CI/CD and DevSecOps practices, monitor and improve platform performance, and support analytics and real-time ingestion needs.

As a Data Engineer, you will enhance and maintain data platforms, design data pipelines, and monitor performance while collaborating with stakeholders to manage data responsibly.

Design, build and maintain ETL pipelines and data warehouse solutions on Snowflake. Implement data models and transformations using SQL, Python and DBT. Work with Azure cloud services, engage stakeholders, and deliver data platform solutions in a consulting/client-facing environment.

As a Data Engineer at Intelligen, you'll design and deliver scalable data solutions across multi-cloud environments, developing data models and collaborating with clients to address data challenges.

The Data Engineer will build and scale data infrastructure, design data processing systems, and collaborate with teams to optimize data quality and performance using various GCP technologies.

As a Software Engineer, you'll develop and maintain data acquisition pipelines, ensuring quality and performance in data integration. You'll work on both batch and streaming ingestion while collaborating across domains.

As a Staff Machine Learning Engineer, you'll design and operate AI infrastructure, focusing on MLOps practices, security, and collaboration with data scientists to deliver scalable AI features.

As a Senior Data Engineer, you will design and implement data transformation pipelines, gather business requirements, and work with various big data technologies.

The role involves designing and building data models for analytical insights, optimizing queries, and collaborating with data scientists on production models.

Lead design and delivery of enterprise-scale Azure data platforms. Architect ADF pipelines, Snowflake data models, and dbt transformations. Provide technical leadership, mentor engineers, implement data quality/lineage/governance, and engage stakeholders to translate business needs into scalable solutions.

The Software Engineer will manage data collection for model training, enhance the ingestion pipeline, and collaborate with the AI team on data strategy.

The Staff Data Engineer designs and operates scalable data platforms, leads technical practices, and enhances delivery performance within the AI & Analytics Data Products team.

Plan and execute rolling upgrades across tens of thousands of ClickHouse clusters, own the full release pipeline, investigate and resolve production issues (including on-call), and build automation and tooling to make large-scale database operations safer and repeatable while collaborating with core database and cloud infrastructure teams.