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Board of Australian Finance Group

Board of Australian Finance Group is hiring: Data Analyst in Snowflake

Board of Australian Finance Group, Snowflake, AZ, United States, 85937

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Overview

We’re seeking a skilled and curious Data Analyst to join our team and help drive data-led decision-making across the business. You’ll work closely with the business to explore complex datasets, build reports, uncover actionable insights, and deliver high-impact analytics solutions that improve business performance.

Main Duties & Responsibilities

  • Perform exploratory analysis of complex datasets to identify trends, patterns, and opportunities for improvement.
  • Collaborate with stakeholders to understand business challenges and translate them into data-driven solutions.
  • Collect, clean, and model data from multiple sources to support strategic decision-making.
  • Design, build and deliver interactive dashboards and visualisations using Power BI and other tools.
  • Monitor and optimise the performance of productionised datasets and analytics models.
  • Create and maintain comprehensive documentation of data models, transformation logic, dataset architecture, and report design to ensure transparency, reproducibility, and effective knowledge sharing.
  • Address ad-hoc data requests and incidents with high-quality, complete and timely solutions.
  • Leverage DBT (Data Build Tool) to design and implement robust data models to transform raw data into structured, analysis-ready datasets that support accurate reporting and decision-making.
  • Collaborate effectively within a team of data analysts to share knowledge, align on best practices, follow processes and deliver cohesive, high-quality analytical outputs that support business objectives.

Skills and Experience

  • Tertiary qualifications in Data Science, Statistics, Computer Science, or a related discipline.
  • Minimum 2 years’ experience in data analysis or a related field.
  • Proficiency in SQL for data manipulation, querying, and modelling.
  • Proficiency in data visualisation tools such as Power BI.
  • Experience with cloud-based solutions such as Snowflake.
  • Strong analytical and problem-solving skills.
  • Ability to manage multiple priorities and deliver high-quality work in a fast-paced environment.
  • Ability to communicate insights clearly to technical and non-technical audiences.
  • Experience with programming languages such as R and Python.
  • Familiarity with structured and semi-structured data formats (e.g., JSON, XML).
  • Experience with statistical analysis and/or machine learning techniques.

About AFG

Australian Finance Group (ASX:AFG) is one of Australia's largest mortgage broking groups, founded back in 1994 and now employing 300+ staff across Australia. As a category leader, AFG has some 4,000 finance brokers in its network with access to over 10,000 financial products from more than 80 of Australia’s leading lenders.

Through our broker network, AFG processes around one in 10 of all Australian residential mortgages and manages over $214 billion in residential and commercial finance.

In addition to our broker network, AFG has a rapidly growing home loan business, and an expanding footprint in the provision of business lending solutions.

Our purpose is to create a fairer financial future for all. Our culture is innovative, entrepreneurial and collaborative, underpinned by our values of integrity, accountability, customer-centric and team player (IACT). We encourage people with ideas and a willingness to learn to join us. AFG is committed to an inclusive workplace where all are welcomed and recognised for their unique abilities.

Application Questions

Your application will include the following questions:

  1. How many years' experience do you have as a data analyst?
  2. Which of the following statements best describes your right to work in Australia?
  3. What’s your expected annual base salary?

To help fast track investigation, please include here any other relevant details that prompted you to report this job ad as fraudulent / misleading / discriminatory / salary below minimum wage.

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