About the role
We're hiring a Data Engineer I — someone who'll join fast-moving team that built our enterprise data lake from the ground up and now owns the full stack: data lake, data warehouse and the platform that keeps it all running. We're looking for someone energetic and self-motivated someone who can manage their own tasks, ask good questions and build real confidence quickly in a team that trusts you to do exactly that. This isn't a role where work gets handed to you. You own your progress here.
What you'll do
Contribute to the design and development of new data applications and systems that meet the requirements of our Data and Analytics environment2
Analyse business and system requirements to better understand what the data environment needs3 — and help build solutions that address them
Work with architects to contribute to solution design documentation for new and existing data products and systems4
Write and maintain ETL processes across our data lake and data warehouse
Apply Agile practices, testing standards and data governance principles to everything you build
Get exposure to AI tooling development — including MCPs, proxies and operational models — as your skills grow
Education (Minimum)
A relevant tertiary qualification in Information Technology or Data Analysis
Knowledge and Experience
Knowledge:
Minimum:
Must have detailed knowledge of:
IT systems development processes (SDLC)
Application development
ETL processes
Rational database system and cloud data warehousing
Dimensional modelling
Standards and governance
Agile development life cycle
Testing practices
Ideal:
Knowledge of:
Data analysis and design
Data architecture (technical design and implementation processes)
DPLC
Solid understanding of:
Banking systems environment
Banking business model
Best practices for Quality Assurance (QA)
Experience:
Minimum:
A relevant tertiary qualification in Information Technology or Data Analysis5
At least 2 years of solid Python experience — this is the core technical requirement for the role
Foundational SQL knowledge
Exposure to AWS — or another cloud platform such as Azure or Google Cloud Platform
Proven experience with SQL Server and/or business intelligence tools (SSIS, SSRS or SSAS), data warehousing and the data management lifecycle5
An understanding of IT systems development processes (SDLC), ETL, relational databases, cloud data warehousing and Agile methodologi
Proven experience with SQL Server and/or business intelligence tools (SSIS, SSRS or SSAS), data warehousing and the data management lifecycle5
Ideal:
Proven experience in:
Python and/or Open Source development tools
Visualisation Technologies: MS PowerBI, AWS QuickSight
Cloud Environment
Experience working in an AWS environment as well as with AWS Technologies
