Key Responsibilities

- Design, build, and maintain scalable data pipelines and data integration solutions
- Develop and optimise ETL/ELT processes to ingest, transform, and store data from multiple sources
- Work closely with data architects, analysts, and downstream consumers to deliver reliable data solutions
- Implement data processing solutions across batch and near-real-time use cases
- Ensure data quality, reliability, and performance across data platforms
- Support cloud-based data platforms, data lakes, and data warehouses
- Apply data security, privacy, and access control requirements across data solutions
- Troubleshoot and resolve data pipeline failures and performance issues
- Contribute to automation, monitoring, and continuous improvement of data engineering practices

Required Skills & Qualifications





- 5+ years’ experience in Data Engineering or data-focused engineering roles
- Strong experience with ETL/ELT development and data pipeline orchestration
- Solid proficiency in SQL and experience with relational and NoSQL data stores
- Experience with cloud data platforms (e.g. Azure Data Factory, Databricks, Synapse or equivalent)
- Experience working with structured and semi-structured data
- Familiarity with data modelling concepts and performance optimisation techniques
- Experience with CI/CD pipelines and DevOps practices for data solutions
- Robust analytical, problem-solving, and troubleshooting skills

📌 Database Engineer (Sydney)
🏢 Indigitise
📍 Sydney