Data Engineer

Morgan McKinley; Sydney; On-site; AUD 90,000 - 120,000; Part time

Job summary

Morgan McKinley is seeking a Data Engineer for a 6-month contract in Sydney to strengthen cloud data capabilities across ingestion, transformation and reporting.

You will build and maintain pipelines to a cloud data warehouse, optimize performance, migrate legacy data, and enable trusted analytics with Power BI and AWS services. Collaboration with business and technology teams, plus mentoring junior engineers, are key aspects.

Qualifications

• Commercial experience as a data engineer.
• Strong SQL with complex queries and stored procedures.
• Hands-on ETL/ELT development and data modelling.
• Cloud data experience, with AWS.
• Experience moving data from legacy platforms to the cloud.
• Experience supporting BI reporting, ideally Power BI.
• Comfort with automated data testing and agile ways of working.
• Background in financial services (banking, insurance, wealth or lending).
• Ability to explain data issues clearly to technical and business audiences.

Responsibilities

• Build and maintain pipelines from source systems into the cloud data warehouse.
• Monitor pipeline performance and diagnose data issues.
• Shape data structures for reporting and analytics teams.
• Migrate older on-premise data and logic to the cloud.
• Collaborate with business and technology teams to design data solutions.
• Support less experienced engineers through code reviews and pairing.

Skills

SQL

ETL/ELT

Data modelling

BI reporting

Agile

Data testing

Tools

Power BI

Airflow

AWS

Redshift

S3

Job description

Data Engineer

Contract - 6 Month

Immediate start

Opportunity

We are working with an exciting FinTech who are looking to strengthen their cloud data capability. You will work across ingestion, transformation and reporting data, helping the business trust its numbers and get to them faster.

What you will be doing

• Building and looking after the pipelines that bring data from source systems into the cloud warehouse.
• Watching how those pipelines perform and where data goes wrong, then fixing the underlying cause.
• Shaping data structures that reporting and analytics teams can use with confidence.
• Helping shift older on-premise data and logic onto the cloud platform.
• Working with business and technology teams to understand what they need from data and how it should be designed.
• Supporting less experienced engineers through code reviews and pairing.

What you will bring

• Proven commercial experience as a data engineer.
• Strong SQL, including complex queries and stored procedures.
• Hands-on ETL / ELT development and data modelling.
• Cloud data experience, with genuine exposure to AWS.
• Involvement in moving data from legacy platforms to the cloud.
• Experience supporting BI reporting, ideally Power BI.
• Comfort with automated data testing and agile ways of working.
• A background in financial services such as banking, insurance, wealth or lending.
• The ability to explain data issues clearly to both technical and business audiences.

Desirable

• Python or PySpark.
• Workflow orchestration tools such as Airflow.
• AWS data services such as Glue, Redshift, S3 or Athena.
• Data quality or data testing frameworks.
• Data governance, cataloguing or handling sensitive customer data.