Top Data Engineer Jobs in Melbourne

Design, build, and operate scalable data platform pipelines and models using Snowflake, dbt, Prefect, Flink and AWS. Own end-to-end platform components, apply IaC with Terraform, implement CI/CD and testing, manage production systems, monitoring and incident response, and improve data quality and self-service capabilities for downstream teams.

Manage and optimise on-prem SQL Server systems, design and run hybrid ETL/ELT pipelines to AWS/GCP, integrate SaaS APIs (e.g., Genesys), tune query performance, implement orchestration (MS Agent), and ensure secure, governed data movement.

Design, build, and maintain scalable data pipelines and Delta tables using Microsoft Fabric and Python/Spark SQL. Optimize datasets for Power BI, monitor data quality, support CI/CD and deployments, manage Fabric performance and security, and document operational runbooks.

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.

Design, build and optimise cloud data platforms and lakehouse solutions on Microsoft Azure and Microsoft Fabric. Develop scalable ETL/ELT pipelines, data models, and transformations using SQL, Spark and Python. Implement data governance, security, CI/CD and collaborate with stakeholders to enable analytics, reporting and AI use cases.

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.

Lead design, build and optimise enterprise data platform and pipelines (Microsoft Fabric migration, AX ERP modelling, Denodo). Ensure platform performance, governance, incident management, and mentor junior/offshore engineers while driving stakeholder delivery in an agile environment.

Design, build, and maintain data pipelines and core customer datasets to consolidate legacy systems into a unified customer profile. Collaborate with data engineers, analysts, and cross-functional squads to ensure data accuracy, remediation, and enable personalization and ML capabilities. Work in a small, dynamic team operating within a hybrid Melbourne-based environment.

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, build, and maintain scalable, fault-tolerant GCP data pipelines and BigQuery data models. Collaborate with data scientists and engineers to ensure data quality, monitor production systems, implement CI/CD for pipelines, and recommend cloud data architecture and governance improvements.

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.

Hands-on data engineer working with clients to re-engineer, optimise and domain-align data models and pipelines using Snowflake and dbt. Contribute to solution design, performance tuning, CI/CD, testing, documentation, and collaborate within consulting delivery teams to ensure maintainability and lineage.

Lead architecture and delivery of scalable data solutions across squads. Design and optimise ETL/ELT workflows, mentor engineers, collaborate with data scientists and stakeholders, drive data modelling, orchestration, governance and strategic roadmap for the data platform.

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

Lead design and build scalable data platforms and ELT pipelines using Databricks or Snowflake and dbt. Design architecture across ingestion, storage, modelling and consumption layers, optimise performance, configure platform components, implement CI/CD, automate testing and monitoring, manage vendor relationships, support data quality and lineage, and mentor junior engineers while enforcing engineering best practices.

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, cloud-native software and data/AI-enabled platforms for Business Banking. Build APIs, services and platform capabilities, drive architecture and engineering standards, mentor engineers, champion CI/CD, observability and DevSecOps, and support production platforms to deliver customer and colleague digital experiences.

Lead architecture and delivery of AI-enabled CRM, customer engagement and banker experience platforms. Drive platform strategy across cloud, APIs, workflow orchestration and AI, establish engineering standards, ensure security/privacy/responsible AI, mentor engineers, and influence stakeholders to deliver scalable, resilient customer and colleague experiences.

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.

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.

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

The Senior Data Engineer/Consultant will lead data engineering projects, ensuring high-quality technical outcomes using Databricks, while mentoring team members and collaborating with clients.

Lead design and delivery of modern cloud data platforms and scalable pipelines. Improve platform stability, implement data models and governance, support data product development, mentor junior consultants, and collaborate with stakeholders to translate business needs into reliable, automated data solutions.