Senior Data Engineer

Russell Tobin; Sydney; On-site; AUD 180,000 - 240,000; Full time

Job summary

Russell Tobin is seeking a senior data engineering professional to lead modernization of on-premise databases to cloud-native AWS solutions, including Aurora PostgreSQL, Glue ETL, and Redshift analytics. The role focuses on transforming SSIS/SSAS workloads, building scalable ingestion pipelines, and delivering robust data models.

You will collaborate with architects and business stakeholders to ensure data quality, governance, and successful migration outcomes, with emphasis on CI/CD for

Qualifications

• 5+ years' experience in Database and Data Engineering.
• Strong expertise in SQL and database performance tuning.
• 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.

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.

Skills

SQL

Database Engineering

Python

PySpark

ETL/ELT pipelines

Cloud Data Solutions

CI/CD DevOps

Data Governance

Data Modelling

Analytics & Reporting

Tools

AWS Glue

Amazon Redshift

AWS Quick

AWS DMS

Schema Conversion Tool

Job description

• 5+ years' experience in Database and Data Engineering.
• Strong expertise in SQL and database performance tuning.
• Experience with AWS data services including :
• AWS Glue
• Amazon Redshift
• AWS Quick
• AWS DMS and Schema Conversion Tool (desirable)
• Strong 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.