DQAA Senior Data Analyst

Enterprise Technology provides reliable, secure and resilient technology services and solutions to support EY people. As part of Enterprise Technology, you’ll be at the forefront of enabling innovative technologies and world-class technology infrastructure.

Our aim is to build outstanding customer experience with clear investment in innovation, alongside operational excellence that delivers efficient, quality services and solutions.

The opportunity

The CBS Data Office is responsible for enabling foundational data management capabilities across CBS, including Data Quality Analysis & Advisory (DQAA). The DQAA focus area is designed to identify, analyze, and help remediate data quality issues that impact business processes, reporting, compliance, and downstream analytics across CBS functions

As a Senior Data Analyst, you will play a hands‑on technical role, leveraging a range of data analysis, automation, and visualization tools to perform data quality assessments, support collaboration across CBS functions, and help mature CBS‑wide data quality capabilities. This role combines deep technical data quality analysis with the ability to identify patterns, enabling stakeholders to understand root causes, impacts, and remediation options for data quality issues.

Your key responsibilities

• Perform data quality profiling, validation, and analysis across CBS datasets to identify defects, anomalies, and trends impacting business outcomes.
• Leverage tools such as Alteryx, SQL, and other analytics platforms to analyze large datasets and surface data quality issues efficiently.
• Design and maintain repeatable data quality workflows and automations using tools such as Power Automate and Alteryx to improve efficiency and scalability of analysis.
• Develop Power BI dashboards and reports to communicate data quality findings, trends, and remediation progress to stakeholders.
• Partner with CBS function stakeholders to translate data quality findings into actionable insights, supporting remediation planning and prioritization.
• Support issue management and remediation efforts, including documentation of root causes, impacts, and recommended solutions.
• Support alignment of data quality activities with broader CBS Data Office capabilities, including Data Governance, GDT&C, and MDM.
• Learn and support usage of vendor platforms with data quality capabilities, such as Collibra, Profisee MDM, and other emerging tools, as they are adopted within CBS.
• Contribute to data quality frameworks, playbooks, and documentation, supporting consistent execution and knowledge transfer across the CBS Data Office.

Skills and attributes for success

To qualify for the role, you must have

• Strong hands‑on experience performing data analysis and data quality assessments in an enterprise environment.
• Proficiency with SQL for querying and analyzing structured datasets.
• Experience leveraging Alteryx (or similar analytics tools) for data profiling, transformation, and quality analysis.
• Experience building Power BI dashboards and reports to communicate analytical insights.
• Familiarity with Power Automate or similar tools to support automation of data processes.
• Strong problem‑solving skills with the ability to identify root causes and articulate data quality impacts clearly.

Ideally, you’ll also have

• Exposure to data quality, metadata, or governance capabilities within vendor platforms such as Collibra and Profisee MDM.
• Experience supporting data quality remediation initiatives in collaboration with business and technology stakeholders.
• Familiarity with CBS‑like enterprise data environments and cross‑functional data dependencies.
• Ability to learn and adopt new tools and technologies to support evolving data quality use cases.
• Experience applying AI/ML techniques (e.g., anomaly detection, pattern recognition, clustering) to enhance data quality profiling, defect identification, and trend analysis across large, complex datasets.
• Ability to leverage AI‑assisted analytics tools to accelerate root‑cause analysis, identify hidden data quality issues, and prioritize remediation based on business impact.
• Familiarity with using AI‑driven rules suggestion or metadata enrichment capabilities within data quality, MDM, or governance platforms to improve scalability and consistency of data quality controls.

What we look for

• A technically strong, execution‑oriented analyst who is comfortable working hands‑on with data and tools.
• A structured thinker who can translate complex data issues into clear insights and recommendations.
• A collaborative team member who can partner effectively with governance, risk, and technology stakeholders.
• A continuous learner who is curious about emerging data quality, automation, and analytics tools.
• A professional who values data accuracy, transparency, and operational discipline.