The Client:
Australian financial services leader with a technology-first approach.
Backed by significant investment in the latest technologies, we’re redefining possibilities through advanced, data-driven innovations.

The Role:

- Build and optimise data models using DBT, ensuring high performance and scalability.
- Leverage Python to enhance workflows, automate processes, and integrate data sources.
- Design and deliver operational efficiencies in an AWS Cloud environment
- Translate large, disparate data sources and implement modern data architecture practices
- Empower Data Engineering teams with solution design and development of sustainable data products.
- Address and resolve data access, visualization, and reporting challenges with robust solutions.
- Collaborate with stakeholders to understand data needs and translate them into business requirements




- Deliver strategic data outcomes and influence the data analytics strategy

This is a Hybrid working environment : 3 days in office / 2 days WFH

Ideally, you will have:

- 7+ years experience in data management, data modelling, data warehousing, and data architecture in modern cloud-based data platforms (AWS preferred)
- Extensive commercial experience in DBT (Data Build Tool) for data transformation, modeling, and analytics.
- Strong knowledge of AWS Redshift in an enterprise setting
- Full Australian working rights are required for this role

email [email protected] for a confidential discussion. -
THE ARGYLE NETWORK
Finding the best talent for the Australian FinTech industry
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📌 Senior Data Analytics Engineer - DBT (Sydney)
🏢 The Argyle Network
📍 Sydney