Data Platforms Business Analyst

More than 45 years ago, John C. Bogle had a vision to start an investment company that did things differently. A company with no external shareholders. Where all the profits were invested back into the business and used to lower costs. To this day, Vanguard Group still has no external shareholders. That means no share prices to protect and no profits to generate for outside owners.

Today, Vanguard is one of the world's largest investment management companies, serving more than 50 million investors worldwide. For nearly 30 years Vanguard Australia has been supporting individual investors, financial advisers, and superannuation members to achieve their long-term financial goals.

Hybrid role (in office Tues-Wed-Thurs) • Melbourne, VIC

Join our growing Data Platforms team within the Chief Data & Analytics Office . You will help shape how Vanguard designs, delivers and optimises data , E nabling trusted, high - quality, AI - ready data for our business .

What You'll Do

In this role, you will be a core bridge between business needs and technical data engineering delivery, contributing to both functional analysis and hands - on solution support.

You will:

• Partner closely with our data engineers to understand business requirements and translate them into clear, structured user stories and documentation.

• Support analysis for the design, build and rollout of modern cloud - based data solutions, including AWS and Databricks.

• Facilitate requirement - gathering sessions with stakeholders across Vanguard.

• Partner with the product owner to h elp maintain product backlogs by organising work, validating priorities and ensuring clarity of acceptance criteria.

• Assist with data quality investigations, root - cause analysis and process improvements.

• Contribute to governance, documentation, and operational readiness for new datasets and pipelines.

• Work with the team to turn complex technical concepts into business - friendly insights and artefacts.

• Support reporting, metrics and continuous improvement initiatives aligned with Data Engineering principles.

• Minimum three years of relevant work experience , including one year in technical writing or business technology

• Undergraduate degree or equivalent experience; Data related degree preferred

• Strong analytical and problem - solving skills with the ability to translate business needs into technical requirements

• Strong SQL skills

• Exposure to data engineering concepts ( e.g. Data lakes, Data Models and analytics)

• Exposure to Data Modelling concepts ( e.g. ERDs, dimensional modelling, S tar S chemas)

• Strong ability to produce documentation ( e.g. Source to target mapping, data dictionary creation and process documentation)

• Experience with data reconciliation and validation

• Excellent written and verbal communication

• Ability to work collaboratively with technical and non-technical stakeholders

• Experience writing user stories, process maps or business requirements

• Financial services or investment management experience.

• Familiarity with cloud platforms (AWS and Databricks ideal), databases or data tooling.

• Knowledge of data lifecycle concepts (ETL, data quality, metadata , governance ).

• Experience with Agile delivery or JIRA/Confluence.