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.

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.

Design, build and maintain scalable data pipelines and Delta tables using Microsoft Fabric, Python and Spark SQL. Optimize datasets for Power BI, implement data engineering patterns (incremental loads, merges, validation), support CI/CD and monitor data quality, performance and security. Document solutions and runbooks and collaborate with stakeholders across the business.

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.

Lead design and delivery of cloud-native data platforms and pipelines for regulatory reporting. Build reusable data assets, integrate diverse sources, enforce coding standards, mentor engineers, and ensure scalable, high-performance, reliable data solutions on AWS/Snowflake.

Design and build scalable data platform solutions from ingestion to modelling and infrastructure. Own end-to-end technical problems, improve data quality and observability, implement IaC and CI/CD, manage production systems (monitoring, incident response), and enable self-service analytics for downstream teams using modern tools like Snowflake, dbt, Prefect, Terraform, AWS and real-time tech.

Lead architecture and technical direction for real-time streaming and analytics. Own data ingestion, streaming, modelling, warehousing and data apps. Influence cross-team standards, mentor engineers, review designs, and improve operational reliability and DataOps to deliver scalable, secure data products.

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.

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.

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.

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.

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, develop, and maintain ELT/ETL Snowflake data warehouse solutions; implement data standards, CI/CD, monitoring, and production support; collaborate with product, business, and vendors; mentor junior developers and improve data engineering practices.

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, build and optimise cloud-native, enterprise-scale data platforms and pipelines using Snowflake and AWS. Deliver trusted analytics-ready datasets, improve performance/resilience, drive automation and engineering best practices, support production systems, and mentor colleagues to enable analytics, AI, fraud detection and customer intelligence.

Design, build and operate Snowflake‑centric cloud data platforms and scalable ETL/ELT pipelines. Drive DataOps practices, data quality, governance, security, and observability. Influence architecture, mentor peers, and deliver fit‑for‑purpose analytics solutions in a regulated enterprise environment.

Design and build scalable cloud-native data pipelines on AWS and Snowflake to support financial crime monitoring, reporting and insights. Collaborate with engineers and stakeholders to deliver secure, resilient data products, implement CI/CD automation, and ensure data governance and quality.

Lead design and delivery of scalable AWS-native data platforms and pipelines. Build data products using Glue, Iceberg, Redshift, Airflow and related tooling. Provide technical leadership, governance, automation, and mentoring to a team of data engineers while ensuring security, cost-effectiveness, and cross-team collaboration.

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.

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.

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.