Summary
✨ AI‑Generated
A senior data engineering role focused on migrating legacy data platforms to cloud-native architectures, building ETL pipelines, and optimizing analytics solutions.
Highlights
Work on large-scale cloud data modernization projects, building scalable data solutions and improving analytics capabilities.
Description
Role : Senior Data Engineer – Cloud Data Modernisation
Location: Sydney
Duration: Permanent
Role Purpose
We are seeking an experienced Senior Data Engineer to support the modernisation of a legacy Microsoft SQL Server data platform to AWS-native services.
The role will focus on modernising databases, ETL pipelines, data warehousing, and reporting solutions, transitioning from MS SQL Server, SSIS, SSRS, and SSAS to Amazon Aurora PostgreSQL, AWS Glue, Amazon Redshift, AWS data capability/ SnowFlake.
The successful candidate will design, build, and optimise scalable cloud-native data solutions while ensuring data quality, performance, and operational stability.
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.
Required Skills & Experience
5+ years' experience in Database and Data Engineering.Strong expertise in SQL and database performance tuning.Experience with AWS data services including:Amazon Aurora PostgreSQLAWS GlueAmazon RedshiftAWS QuickAWS DMS and Schema Conversion Tool (desirable)Strong SQL and data modelling skills.Proficiency in Python and/or PySparkExperience 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.
Success Measures
Successful modernistion /migration of data assets from Microsoft technologies to AWS-native services – AWS aurora, Glue, RedshiftDelivery of scalable, reliable, and cost-effective cloud data solutions.Improved automation, performance, and maintainability of data pipelines and reporting platforms.Adoption of modern analytics capabilities through Redshift, AWS data capabilities and Snowflake
