Desirable
5+ years' experience in Database and Data Engineering.
Robust 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)
Robust 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