Top Data Engineer Jobs in Sydney

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.

Build, maintain and scale production data pipelines and platforms on GCP (BigQuery, Dataflow, Cloud Storage). Improve data quality, observability, governance and self-service capabilities; partner with engineers, analysts and product teams to design data models and datasets that inform business decisions.

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.

Hands-on data engineer to re-engineer and optimise dbt models and Snowflake data warehouses. Responsibilities include schema design, performance tuning, domain-aligned modelling, CI/CD, testing, documentation, and collaborating with client teams and consulting peers to deliver maintainable pipelines.

The Data Engineer will design and manage data processing systems, transforming raw data into actionable insights by building scalable pipelines on Google Cloud Platform technologies.

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.

Lead design and delivery of scalable AI and data platforms including LLM and agentic systems, RAG, and Databricks-based lakehouse architectures. Architect batch and streaming pipelines, implement MLOps/DataOps, establish standards and guardrails, embed Responsible AI and governance, and mentor engineers while driving cross-functional delivery and platform reliability.

Design, build, and maintain petabyte-scale ETL/ELT data pipelines and BigQuery data models on GCP. Collaborate with data scientists and engineers to ensure data quality, implement CI/CD for pipelines, monitor production systems, and recommend new cloud data technologies. Support streaming data processing and infrastructure-as-code for secure, scalable solutions.

Design and deliver governed, scalable data products and a unified semantic layer across Finance, People, Procurement, and Compliance using Databricks, dbt, SQL, and PySpark. Implement end-to-end governance (Unity Catalog, column-level security, lineage, PII handling), drive DataHub metadata adoption, and set engineering standards for CI/CD, testing, observability, and data quality. Translate senior-stakeholder requirements into production-grade solutions used for reporting, analytics, and AI.

Senior developer responsible for driving development of MYOB's SaaS platform, building web services and integrations, deploying cloud solutions (Azure/AWS), implementing TDD, DevOps, event-driven architecture and CI/CD, and collaborating with the Data & AI team to deliver AI-powered features and scalable, resilient systems.

Provide configuration and technical data management services: version control, baselining, governance of engineering artefacts. Ensure lifecycle and audit compliance, use CM tools and processes, and share knowledge with customers and stakeholders.

Lead design and delivery of cloud data platform solutions for banking clients. Own solution design, data modelling, ETL/CI-CD, SQL development, stakeholder engagement, and lead technical project delivery.

Lead design and delivery of scalable data architecture and pipelines. Build, maintain and optimise ETL/data infrastructure, collaborate with stakeholders to translate requirements, ensure data quality and performance, and adopt modern data engineering practices and tools to enable trusted, business-ready datasets.

Design, build and maintain scalable cloud data pipelines and warehouses. Improve performance, ensure data quality and governance, support AI/ML initiatives, document systems, and collaborate with cross-functional teams while mentoring engineers.

Design, build, and operate scalable cloud-based data platform and infrastructure. Develop high-throughput ELT/ETL pipelines, optimize SQL databases, ensure data quality/security, support analytics and AI initiatives, troubleshoot production issues, and document systems.

Own and maintain Blinq's data analytics infrastructure and pipelines. Integrate data from multiple sources, build ETL processes, enforce data quality and validation, design scalable data processing systems, maintain dashboards, and partner with Product and Engineering to enable data-driven decisions and reporting.

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.

Design, build and operate scalable Lakehouse data platform and batch/real-time pipelines. Develop data assets, streaming solutions (Kafka/Flink), ETL/ELT workflows (Airflow, DBT), and cloud-native architectures on AWS, Snowflake and Databricks. Optimize SQL and Spark workloads, manage schema and performance for Iceberg tables, enforce data quality and governance, and partner with data science, analytics and product teams to deliver cost-efficient, reliable data solutions.

Design, build, and operate scalable batch and real-time data pipelines and Lakehouse data assets using AWS, Snowflake, Databricks, Kafka, and Flink. Collaborate with data science, analytics, and product teams to ensure data quality, modelling, governance, performance, and cost-efficiency.

Design and lead a cloud-agnostic enterprise data ingestion framework: author solution designs, build and optimize batch/streaming pipelines, embed data quality/lineage/security, and guide engineering squads for scalable multi-cloud data platforms.

Join Speechify's AI team as a Software Engineer responsible for data collection and infrastructure management to enhance model training operations.

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.

Design and maintain scalable data pipelines and real-time streaming systems on AWS, enable ML/LLM-powered customer features, integrate Amazon Bedrock and models into agentic workflows, automate ML lifecycle steps, collaborate with ML, data science, and product teams to ship production-grade solutions.

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.