Top Data Engineer Jobs in Melbourne

Design, build, and support reliable, scalable data pipelines and infrastructure. Prepare structured data and metadata for AI/analytics, ensure data quality and governance, collaborate with engineers, data scientists and analysts, and drive continuous improvement and observability across the data platform.

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.

The Principal Data Engineer will architect cloud-native platforms, oversee model execution and data management while ensuring compliance with regulatory standards in a high-performing team.

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 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.

The Software Developer - Data Engineer will build ETL packages, develop scripts, and automate processes while ensuring data security in cloud environments.

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.

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

Design and build high-performance Java microservices and data pipelines to parse, transform, and analyze multi-chain on-chain data in real time. Integrate with Kafka, Redis, RDS, and data lake systems; optimize low-latency computation for token prices, swaps, liquidity metrics; ensure fault tolerance, observability, and alignment with long-term data platform strategy.

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.

Design, build, and maintain scalable, observable data pipelines and metadata frameworks to support analytics, AI/ML, and BI. Collaborate with engineers, data scientists, and analysts to improve data quality, governance, and delivery efficiency while driving best practices and MLOps integration.

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.

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

The Principal Engineer, Data & Platforms role involves overseeing the enterprise data platform, driving architecture and performance, and embedding AI capabilities while ensuring security, governance, and compliance.

As a Senior Data Engineer, you will design and build scalable data products, maintain data pipelines, ensure data quality, and mentor junior engineers in a collaborative environment.

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.

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