Top Data Engineer Jobs in Melbourne

Design and deliver scalable multi-cloud data solutions using Databricks/Snowflake and modern data stacks. Build ingestion, transformation, modelling and access layers, implement dbt and CI/CD, ensure data quality, governance and lineage, support analytics and AI enablement, and consult directly with clients while mentoring junior engineers.

Design, develop, and maintain scalable ETL/ELT data pipelines and integrations across cloud platforms (AWS/Azure). Work with data architects and stakeholders to support analytics, reporting, data quality, governance, and modern data architectures (data lakes/warehouses).

In this role, a Data Engineer will develop and maintain data pipelines, implement quality checks, enhance reporting processes, and collaborate with stakeholders.

Kogan.com seeks a Data & ML Engineer to develop data pipelines, support ML workflows, and ensure data integrity for eCommerce operations.

The Principal Data Engineer will design and deliver scalable data architectures, optimize data pipelines, and guide clients in data management strategies. Responsibilities include technical leadership, collaborating with teams, and translating complex concepts for diverse audiences.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

Build and own Overflow's data infrastructure: design ETL/ELT and CDC pipelines, data warehouses, OLAP schemas, and a unified data layer. Enable self-service analytics and dashboards, implement Databricks Unity Catalog for governance, ensure data quality and monitoring, and partner with Head of AI and cross-functional teams to prepare semi-structured data for MLOps and advanced AI workflows.

Lead design and delivery of scalable data and AI platforms across Azure and Databricks. Architect production-grade ML/LLM solutions (RAG, agentic patterns), build batch and streaming pipelines, formalize medallion/lakehouse standards, implement MLOps/DataOps (CI/CD, monitoring, orchestration), embed Responsible AI and governance, and provide technical leadership, mentoring, and cross-functional delivery.

The Data Engineer will design, build, and manage scalable data pipelines on GCP, ensuring data quality and operational excellence while collaborating with data teams.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Design and maintain StratFin data models, automate reporting and data workflows, build reliable pipelines with testing and monitoring, partner with Finance and Strategy to deliver scalable data products, and establish data quality standards to enable analytics and AI.

Develop, deploy, and maintain LLM pipelines and RAG QA/search systems; design and optimize prompts and multi-agent LLM architectures; operate multi‑GPU/cluster inference; build evaluation pipelines for model quality, bias, and hallucination; collaborate with product and CS teams to integrate conversational AI.

Design, develop, and maintain high-performance, highly available backend services and APIs for Big Data products using Java/Python. Manage full service lifecycle, capacity planning, profiling/benchmarking, troubleshooting, security, and system architecture. Contribute to open-source big data projects and build scalable tools for global operations.

Lead design and implementation of scalable, high-performance backend services for traditional and AI-powered search. Own search architecture, optimize indexing/retrieval/ranking, build reusable frameworks, collaborate with data scientists on LLM-enabled search and agents, and deliver robust, low-latency solutions.

Design and develop high-performance backend services for an AI-powered trading assistant: build AI agent execution, trading order execution, AI sub-account and API key lifecycle management, integrate Binance trading APIs, implement skills/tool-calling frameworks, and ensure scalable, low-latency real-time data pipelines, observability, and security.

Drive development of MYOB's SaaS platform as a senior full-stack developer. Collaborate on building web services and 3rd-party integrations, deploy cloud solutions (Azure/AWS) with scalability and resilience in mind, apply TDD, DevOps, CI/CD, clean code and event-driven architecture, and adapt to evolving technical directions.

Lead delivery and quality of modern web experiences: define front-end architecture and design systems, implement accessible, performant, and secure UI, embed testing and observability, mentor engineers, partner with Product and Design, and improve platform and pipelines for scalability and developer experience.

Lead front-end delivery for SaaS products: define architecture and design systems, implement accessible, performant, and secure React/TypeScript UIs, embed testing and observability, mentor engineers, collaborate with Product and Design, and improve platform/pipeline for developer experience and reliability.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

Lead design, development, deployment, and continuous improvement of cloud-native data and analytics solutions on Azure. Act as a hands-on technical lead building scalable, secure end-to-end data platforms using Spark/Databricks, Python/PySpark, and orchestration tools. Ensure CI/CD, DevOps, automation, code quality, mentor team members, resolve complex technical issues, and collaborate with stakeholders and vendors to drive platform evolution.

Build, deploy, and support cloud-native data and analytics solutions on Azure. Design and maintain data pipelines, ingestion, transformation and integration processes using Apache Airflow. Ensure data quality, monitoring, CI/CD and infrastructure-as-code. Troubleshoot platform issues, collaborate with cross-functional teams, and contribute to platform improvements and documentation.

The Data & Analytics Engineer will integrate data stacks with products, build reports and dashboards, and enhance customer experience using AI-driven insights.

The Data Visualization Developer will create and support dashboards in Power BI, develop SQL scripts, perform regression testing, and troubleshoot existing scripts.

Design and build scalable, secure data platform infrastructure on Databricks and Azure. Implement medallion ETL/ELT pipelines, multi-tenant isolation, graph data integrations, RBAC and privacy controls, CI/CD and observability. Lead architecture, mentor engineers, and align platform capabilities with analytics, BI, and AI teams.

As a Lead Data Engineer, you'll design and maintain platform capabilities, CI/CD pipelines, and cloud infrastructure, ensuring system reliability and developer productivity while utilizing AI tools effectively.