Role & responsibilities

- Design, develop and maintain scalable data pipelines and data processing systems.

- Build and optimise ETL/ELT workflows for extracting, transforming and loading data from multiple sources.

- Develop and maintain data warehouses, data lakes and modern data platforms.

- Integrate structured and unstructured data from internal and external systems.

- Design, implement and optimise database schemas, data models and data storage solutions.

- Work with large datasets to ensure data accuracy, consistency, availability and reliability.

- Develop and maintain batch processing and real-time data streaming solutions.

- Implement data quality checks, validation processes and monitoring mechanisms.

- Collaborate with data scientists, business analysts, software engineers and BI teams to support reporting and analytics requirements.

- Optimise SQL queries, database performance and data processing workloads.

- Implement data security, access controls, governance and compliance measures.

- Deploy and maintain cloud-based data solutions using AWS, Microsoft Azure or Google Cloud Platform.

- Work with distributed processing technologies and big data frameworks where required.

- Identify and resolve data pipeline failures, performance bottlenecks and integration issues.

- Automate data workflows, testing, deployment and operational monitoring.





- Maintain technical documentation, data dictionaries, pipeline specifications and architecture diagrams.

- Participate in technical design reviews and recommend improvements to data architecture.

- Support business intelligence, reporting, machine learning and advanced analytics initiatives.

- Coordinate with cross-functional teams to understand business requirements and translate them into technical data solutions.

- Mentor junior engineers and contribute to technical standards and best practices where required.

Preferred candidate profile

- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, Software Engineering or a related technical discipline.

- 10-20 years of relevant skilled experience in data engineering, data platform development, database engineering or related technical fields.

- Strong hands-on experience designing and implementing production-grade data pipelines and enterprise data solutions.

- Experience working with cloud platforms, data warehouses, ETL/ELT frameworks and large-scale data processing systems.

- Demonstrated ability to troubleshoot complex technical challenges and optimise data infrastructure.

- Experience in enterprise environments, large-scale projects or cross-functional technical teams will be an advantage.

📌 Data Engineer (Australia)
🏢 THE Leaves
📍 Australia