Desirable

- 5+ years' experience in Database and Data Engineering.
- Strong expertise in SQL and database performance tuning.
- Experience with AWS data services including :

*Amazon Aurora PostgreSQL

*AWS Glue

*Amazon Redshift

*AWS Quick

*AWS DMS and Schema Conversion Tool (desirable)

- Solid SQL and data modelling skills.
- Proficiency in Python and/or PySpark
- Experience building ETL/ELT pipelines and cloud-native data solutions.
- Familiarity with Git, CI/CD, DevOps, and Agile delivery practices.
- Understanding of data governance, security, and operational support.

Key Responsibilities

- Modernisation SQL Server databases to Amazon Aurora PostgreSQL.
- Analyse and convert SSIS ETL workflows into AWS Glue jobs and workflows.
- Migrate SSAS models and analytical workloads into Amazon Redshift.




- Rebuild SSRS reports and dashboards using AWS Quick.
- Design and develop scalable data ingestion, transformation, and reporting solutions.
- Develop and optimise data models, schemas, and database performance.
- Build and maintain CI/CD processes for database and data pipeline deployments.
- Implement data quality, monitoring, and operational support capabilities.
- Collaborate with architects, developers, business stakeholders, and reporting teams to deliver migration outcomes.
- Support testing, reconciliation, cutover, and post-production activities.

📌 Senior Data Engineer (Sydney)
🏢 Russell Tobin
📍 Sydney