Investment Data Analyst @ AustralianSuper
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About AustralianSuper
At AustralianSuper, we truly care about our colleagues and support diverse needs. We celebrate diversity, foster growth, and enable flexibility in a blended working environment.
Your New Role
This is a 12-month max-term contract opportunity for an experienced Investment Data Analyst. In this role, you will be responsible for data acquisition, data mastering, and production across multiple investment management platforms ensuring accurate, complete, and timely data delivery to the investment department. You will also enforce data governance policies and guidelines.
- Perform daily control tasks and monitor database updates.
- Maintain and validate securities in portfolio management systems.
- Complete portfolio setup and ongoing maintenance across platforms.
- Investigate and resolve data exceptions and quality issues.
- Liaise with data vendors, custodians, and onshore/offshore teams.
What You Will Need
Minimum 2 years experience in investment management or asset owner environments is required. Familiarity with platforms such as Finbourne - LUSID, Informatica, and desirable platforms like Aladdin, Calypso, MSCI BarraOne, and S&P iLevel is essential. Strong working knowledge of Python, PowerBI, APIs, VBA, and SQL is required, along with an understanding of ETL processes, financial markets, and the distinctions between IBOR, ABOR, and PBOR.
Life at AustralianSuper
AustralianSuper is committed to colleague development, offering ongoing learning, coaching, and training, alongside generous leave entitlements and a flexible working arrangement. The organization champions safety, respect, inclusiveness, and diversity.
Key skills/competency
- Investment Data
- Data Governance
- Portfolio Management
- Data Reconciliation
- ETL
- Python
- SQL
- Financial Markets
- Data Quality
- Platform Maintenance
How to Get Hired at AustralianSuper
🎯 Tips for Getting Hired
- Customize your resume: Highlight investment data and ETL experience.
- Research AustralianSuper: Understand their culture and diversity initiatives.
- Prepare technical examples: Demonstrate proficiency with Python and SQL.
- Practice interview scenarios: Focus on data reconciliation and problem solving.