Data Analyst @ EY
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Overview
At EY, we’re all in to shape your future with confidence. Join a globally connected powerhouse where diverse teams help build a better working world.
The Opportunity for Data Analyst
As our Data Analyst, you will be part of a multidisciplinary team focusing on collecting, combining, and exploring data to create insights that guide client decision-making. You will build data solutions that drive efficiencies within accounting, finance, governance, and regulatory spaces through automation and innovative data analytics techniques.
Key Responsibilities
- Deliver exceptional client service by providing valuable data insights.
- Transform service delivery using technology-driven methods.
- Perform advanced financial analysis and reporting in complex environments.
- Design and develop analytical solutions addressing client inquiries and emerging trends.
Skills and Qualifications
Tertiary qualifications in Business, IT, or STEM with one to two years’ experience in data and analytics. Advanced proficiency in programming, analytics, and data visualisation is required. Experience with tools such as SQL, Python, JavaScript, Power BI/DAX, and familiarity with cloud computing platforms like Microsoft Azure is highly valued.
What We Offer
Enjoy career development in a diverse and inclusive culture, flexible work arrangements, and a comprehensive benefits package including wellness incentives, additional flex leave, and family-friendly policies.
Acknowledgement and DE&I
EY respects the Traditional Owners and Custodians of the lands, and upholds diversity, equity, and inclusiveness. We provide a barrier free recruitment experience and encourage applicants from all backgrounds.
Key skills/competency
- Data Analytics
- SQL
- Python
- Data Visualisation
- Automation
- Financial Analysis
- Client Service
- Problem Solving
- Cloud Computing
- Business Acumen
How to Get Hired at EY
🎯 Tips for Getting Hired
- Tailor your resume: Highlight analytics tools and project experience.
- Research EY's culture: Study mission, values, and success stories.
- Showcase technical skills: Emphasize SQL, Python, and data tools.
- Prepare for interviews: Practice problem-solving and scenario questions.