At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.​

Join EY and help to build a better working world.

We are hiring a high-caliber Senior Data Analyst to join our Assurance team, where you will play a key role in transforming data into actionable insights that drive audit quality and business decisions. In this role, you will work closely with audit professionals, leveraging advanced analytics, data modeling, and automation tools to support assurance engagements. If you are passionate about data integrity, analytical problem-solving, and enabling smarter decision-making through data, we want to hear from you.

Key Responsibilities:

• Collaborate with audit teams to understand data requirements and deliver tailored analytics solutions.
• Extract, clean, and transform large datasets from various sources to support audit procedures.
• Analyze and transcribe financial data into Entity Relationship (ER) diagrams to support structured data modeling.
• Develop dashboards and visualizations using tools like Power BI, Tableau, or Spotfire to communicate insights effectively.
• Apply statistical and analytical techniques to identify anomalies, trends, and patterns in financial and operational data.
• Support the development and deployment of data models and scripts using SQL, Python, and PySpark.
• Ensure data quality and integrity throughout the analytics lifecycle.
• Document processes and methodologies to ensure transparency and repeatability.
• Contribute to the continuous improvement of data analytics capabilities within the Assurance practice.
• Stay current with emerging technologies and trends in data analytics and assurance.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Accounting, or a related field.
• 4+ years of experience in data analytics, preferably within an audit or assurance environment.
• Proficiency in SQL, Python, and Spark/PySpark.
• Strong experience in data modeling and transforming complex datasets into structured formats.
• Experience in the financial sector, with a solid understanding of financial data structures.
• Ability to analyze and transcribe financial data into ER diagrams for structured analysis.
• Excellent problem-solving and analytical skills with attention to detail.
• Ability to communicate complex data insights clearly and effectively to non-technical stakeholders.
• Familiarity with data governance, privacy, and compliance standards.
• Experience working in Agile teams and using project management tools like Jira or Trello is a plus.

Ideally, You'll Also Have

• Familiarity with C#/.NET and Azure cloud services.
• Exposure to the Wealth and Asset Management (WAM) sector.
• Basic knowledge of audit and accounting principles.

What we offer you

At EY, we’ll develop you with future-focused skills and equip you with world-class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more.

Are you ready to shape your future with confidence? Apply today.

To help create the best experience during the recruitment process, please describe any disability-related adjustments or accommodations you may need.

EY | Building a better working world

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

Our offer of employment is contingent upon the successful completion of a background check and pre-screening requirements. The candidate acknowledges that all information provided must be accurate.