The Financial Business Intelligence (BI) Data Quality Analyst is responsible for ensuring that our data and reporting are accurate, complete, and consistent. Primary responsibilities include identifying data quality issues, developing processes to address them, monitoring data quality over time, and creating and maintaining data definitions and documentation. The Data Quality Analyst will also collaborate with data engineers and data scientists to provide quality assurance (QA) for data assets created to support new internal reports.

What you'll do:

• Develop and implement data quality standards and processes, including comprehensive data profiling, reconciliation, and analysis to identify anomalies and inconsistencies in reporting data
• Ensure the integrity of all data consumed or produced by the Finance BI team, and develop formal policies for exception tolerance
• Advocate for and lead proactive initiatives to drive data completeness and quality
• Investigate, analyze, and resolve reported data quality issues
• Develop and maintain internal processes, tools, and documentation repositories to effectively map, prevent, and correct data quality issues
• Analyze problems, identify root causes, formulate findings, and communicate recommended solutions to internal stakeholders
• Collaborate cross-functionally with business users, database developers, and data engineers to resolve data quality issues and implement continuous improvements

What experience you need:

• Bachelor’s degree in Information Systems, Computer Science, Finance, or a related field (or equivalent practical experience)
• 5+ years of experience wrangling, preparing, and transforming complex datasets
• 4+ years of experience analyzing large, multidimensional datasets using advanced analytical tools (e.g., SQL, Python)
• 4+ years of experience applying data governance principles and practices
• 4+ years of experience working within Agile frameworks and product development environments
• 5+ years of experience managing customer or stakeholder relationships, with exceptional communication skills
• 4+ years of project management experience and a self-motivated approach
• 4+ years of experience using self-service data visualization tools (e.g., Tableau, Power BI)
• 1–2 years of experience with BigQuery or equivalent cloud-based big data platforms
  

What could set you apart:

• Proven ability to work independently with strong attention to detail and a focus on execution
• 3+ years of Financial Planning & Analysis (FP&A) experience
• Hands-on proficiency with Python and core data science libraries (e.g., Pandas, NumPy)
• Experience building and managing data pipelines using Google Cloud tools (e.g., Cloud Composer, Dataproc) or real-time data processing tools (e.g., Cloud Dataflow)
• Proven experience working with large-scale datasets, regulatory reporting frameworks, or credit-decisioning workflows within a fintech or financial services environment
• Demonstrated history of using Large Language Models (LLMs) and AI tools to increase daily productivity, workflow efficiency, and deliverable quality

Primary Location:

Function:

Schedule: