Top Data Engineer Jobs in Sydney

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.

Lead Data Engineer / Solution Designer to join a Data Cloud Practice delivering Snowflake-based data platforms for banking clients. Responsible for solution design, data modelling, ETL, dbt pipelines, SQL development, AWS cloud implementation, stakeholder engagement, and influencing technical decisions. Will work across cross-functional teams and may leverage CI/CD, Airflow, ELT tools and Python.

The role involves designing, building, and maintaining scalable data pipelines for analytics, ensuring data quality and reliability, and mentoring other engineers. Requires collaboration with various teams to translate domain requirements into data systems.

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

Senior Data Engineer to support a banking client: design and build Snowflake-based data platforms, implement Iceberg tables, develop dbt models, use AWS (S3, Lambda), create CI/CD pipelines, orchestrate with Airflow. Kafka experience is highly desirable. Initial 6-month full-time contract with hybrid work in Sydney CBD.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

Serve as the primary technical interface for data centre cooling, leading chilled water and liquid cooling solution design, technical pricing, and bid management. Influence early-stage design, ensure performance and resilience, develop cost models and value-engineered proposals, and align cross-functional stakeholders to win complex thermal infrastructure projects.

The Senior Data Engineer will lead data quality assurance, manage and enhance the analytics platform, design self-service data products, deliver analytics capabilities, and mentor junior team members.

Design, build and maintain scalable Azure-based data pipelines, lake/lakehouse and lakehouse architectures. Implement batch and streaming ETL, CI/CD, infrastructure-as-code, performance tuning, governance, and observability. Partner with analytics and AI teams to support analytics and ML workloads and ensure security, privacy and compliance.

This role involves managing data collection for training AI models, integrating infrastructure, and collaborating with scientists to improve data quality and pipeline efficiency.

As a Software Engineer in Data, you will design, build, and support data systems, create real-time data pipelines, and manage data workflows, collaborating across teams.

The Software Engineer will design and implement scalable data pipelines, optimize data processing, collaborate with teams, and mentor junior engineers, focusing on performance and cost-effective solutions.

The Sr Data Engineer will optimize and refactor data pipelines, manage data ingestion from APIs, and support product engineering teams. Responsibilities include design best practices, enhance the modern data stack, and troubleshoot data issues, ensuring resilience and operational excellence.

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.

Build and operate the data infrastructure powering reporting, analytics, and AI. Design and maintain dbt models, Dagster pipelines, and ingestion connectors. Scale AWS-based data infrastructure with Terraform, improve orchestration reliability, enable self-service analytics, enforce data quality via CI/CD and testing, and collaborate with analysts and data scientists to support production ML use cases.

The role involves designing and building scalable systems for trade lifecycle management, maintaining data integrity, and collaborating on reporting pipelines, while also handling production support.

Design and implement scalable cloud-native data architectures, build and optimise ETL and big-data pipelines using Databricks/Spark/Delta Lake, ensure data quality and governance, automate workflows with Python/Scala/SQL, and collaborate with data scientists and analysts to enable AI-driven insights.

The Lead Data Engineer will design and build cloud engineering solutions, lead data infrastructure projects, and mentor the engineering team to enhance data value for clients.

The Senior Data Engineer will engineer and improve enterprise-scale data platforms on AWS, design and build end-to-end data pipelines, and optimize data processing solutions using Apache Spark and Python. Responsibilities include data governance, compliance controls, and collaboration with cross-functional teams to support analytics and data integration needs.

Build and maintain a near real-time financial dashboard by integrating market and forecast APIs, automating financial models, and crafting clear visual narratives using Flourish and Canva. Collaborate with design and marketing partners, ensure data accuracy and performance, and optimize data flows across multiple feeds.