Data Analyst (AI)

Reef Capital Partners•Lehi, UT

4d•$80,000 - $110,000•Onsite

About The Position

Reef Capital is seeking an AI-forward analytics professional to turn business questions into trusted answers for stakeholders across real estate, hospitality, investments, and membership. The analyst will define meaningful metrics and develop dashboards and analyses in Reef Analytics, Reef’s internal analytics application. The role uses AI agents and coding tools such as Claude Code or Cursor as primary development partners, while requiring the analyst to critically review AI-generated code and queries and own the final result. The analyst will take requests from initial clarification through delivery, managing complexity and ambiguity while providing polished, easy-to-use solutions and clear communication. The position works closely with executives and other stakeholders, as well as the Data Engineer, to ensure data is defined, modeled, accurate, governed, and useful for reporting and decision-making. The role also supports self-service reporting, ad-hoc and recurring reports, user training, and ongoing dashboard improvements.

Requirements

Bachelor’s degree in Data Analytics, Business Intelligence, Computer Science, Statistics, Information Systems, or a related field.
At least 3 years of experience in data analysis, business intelligence, or a similar role.
Strong business acumen and the ability to translate complex data into clear, actionable insights for non-technical stakeholders.
Experience building dashboards in Power BI, Tableau, Looker, or a similar BI tool, with a strong grasp of data visualization and dashboard design.
Solid knowledge of SQL for querying and manipulating data.
Familiarity with enterprise applications such as Salesforce, Microsoft 365, and HubSpot, and data platforms such as Snowflake, AWS S3, or data lakes like Microsoft Fabric.
Experience with data modeling, creating data dictionaries, and defining business metrics.
Excellent communication skills, including the ability to present findings clearly to technical and business audiences.
Strong problem-solving, analytical thinking, and attention to detail.
Ability to manage multiple priorities and collaborate effectively in a cross-functional environment.
Familiarity with project management basics such as Kanban, Agile/Scrum, or Waterfall, and tools like Jira.

Nice To Haves

Experience with data engineering tasks.
Experience with Snowflake SQL.
Experience with FinOps or spend analysis, including cloud, software, or AI usage costs.
Experience directly supporting an executive.
Hands-on experience with ETL processes and tools such as Power Query, SQL-based transformations, or integration platforms.
Experience building with Claude Code, Cursor, or similar AI coding tools; eagerness to work with AI coding tools is also welcomed.

Responsibilities

Partner with stakeholders, including executives, to gather and clarify business questions and translate them into defined metrics and analytical solutions.
Own ambiguous data requests by asking questions, filling gaps, and delivering finished solutions.
Provide polished deliverables, clear communication, and follow-through after launch.
Analyze business processes to identify key metrics, KPIs, and opportunities for data-driven improvements.
Define data elements and maintain data dictionaries, glossaries, and metadata.
Design logical and conceptual data models for reporting, analytics, and dashboard requirements.
Validate and test dashboard data for accuracy and consistency before release.
Work with the Data Engineer to resolve data discrepancies and address problems at their source.
Build and maintain dashboards in Reef Analytics using AI coding tools such as Claude Code, Cursor, or similar tools.
Review AI-generated code and queries critically, correct issues, and handle work AI cannot complete independently.
Apply data visualization and dashboard design best practices.
Ship work through Git and GitHub pull requests with code review.
Create self-service reporting solutions that support independent data exploration while adhering to governance standards.
Develop ad-hoc and automated recurring reports for operational and executive decision-making.
Conduct exploratory data analysis to identify insights, trends, patterns, and anomalies.
Provide actionable recommendations based on data findings.
Monitor dashboard usage and performance and iterate based on user feedback.
Support data governance, including documentation of data lineage, security classifications, and best practices.
Partner with the Data Engineer on integrations and pipeline enhancements that improve data availability for analysis.
Train and support end-users in dashboard tools and data interpretation.
Scope, break down, and track work in Jira, including tickets, acceptance criteria, and priorities for people and AI agents.
Manage stakeholder requests, set expectations, sequence work, and communicate progress through delivery.
Turn ambiguous requests into well-defined specifications for AI agents and verify the results.