Sr. Data Analyst, Finance Analytics

About the role

The person in this role will explore large datasets, discover insights, and build reports and interactive dashboards to provide business partners with the information needed to support Asurion Supply Chain Finance/Accounting. The position is responsible for contributing to the design of Asurion’s Finance information architecture, balancing data security, data integrity, report performance, and urgency of customer requests. The candidate should be a quick learner and self-starter who can examine data, model data, query data, and build reporting solutions that communicate insights effectively.

Responsibilities

• Model, develop, and publish Power BI reports, Power Automate Flows, and SSRS reports
• Keep reporting tool knowledge current and adapt to Microsoft updates
• Collaborate with client teams to gather project requirements, align expectations with available resources, and deliver solutions within agreed timelines
• Proactively seek opportunities for process and insight improvement and make implementation recommendations
• Communicate analytical and technical information to project sponsors and senior-level audiences
• Maintain a working knowledge of Asurion’s applications and systems
• Act as a dedicated business partner to assigned business units, proactively engaging stakeholders to understand objectives and deliver solutions that drive measurable outcomes
• Author, validate, and optimize complex SQL queries across enterprise data platforms
• Translate complex analytical findings into clear, outcome-focused narratives tailored to finance leadership and business stakeholders
• Proactively identify opportunities to improve processes, automate repetitive analytical tasks, and enhance insight delivery
• Contribute to the team’s adoption of AI-powered workflows and tooling
• Maintain current working knowledge of company applications, data systems, and system integration patterns relevant to the Finance data environment
• Use and contribute to AI-assisted workflows including enterprise AI tools (e.g., ChatGPT Enterprise, Claude, Microsoft Copilot) to accelerate query development, data documentation, and reporting
• Maintain and contribute to structured data documentation (table references, join logic, schema definitions, relation to business processes, and impact) that supports both human analysts and AI-assisted query development
• Serve as the subject matter expert for assigned business units, building deep knowledge of their data, processes, and reporting needs

Requirements

• Minimum 4-year college degree in Computer Science, Mathematics, Finance/Accounting, Analytics, or IT
• Minimum 4 years of data analysis or business intelligence-related field experience
• Experience with Microsoft Power Stack (Power BI, Power Automate, Power Apps) or equivalents (Tableau, QlikView, Oracle, etc.)
• Strong proficiency with complex SQL language composition and analysis across multiple database platforms
• Proficiency with SQL across multiple dialects and distributed query engines (e.g., Trino/Presto); comfort writing and optimizing queries in large-scale enterprise data environments
• Experience working with large complex data including data modeling
• Strong analytic/problem-solving skills, writing skills, organization skills, prioritization skills, and communication skills
• Capability to participate in multiple concurrent projects

Skills

• Experience with Microsoft Power BI, Tableau, Oracle BI, or equivalents
• Experience with Microsoft SQL Server and writing SQL statements
• Experience with any financial reporting tools (OneStream, Hyperion, etc.)
• Experience working in FP&A, Accounting, Analytics, or general business with exposure to these areas
• Experience with SSRS
• Experience writing code using other programming languages (Python, R, etc.)
• Experience with SSIS
• Experience with Microsoft Power Query
• Experience with Microsoft Dynamics ERP
• Demonstrated experience using AI tools (ChatGPT Enterprise, Microsoft Copilot, or similar) in an analytics or data development context
• Familiarity with prompt engineering concepts and practical application of large language models for data tasks (query writing, documentation, summarization)
• Scripting or automation experience (Python or similar) applied to data workflows, documentation generation, or BI pipeline development