Data Analyst

Phoenix, AZ, 85005

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Type: Direct Placement

Reference ID: 32765578

Date Posted: 08/18/2026



Job Title: Data Analyst
Location-Type: Hybrid, 4 days/week in Phoenix, AZ (must permanently reside currently in AZ)
Start Date: ASAP
Duration: Permanent
Compensation Range: Up to $95,000
Benefits: Eligible for Health, Dental, Vision, 401K
Must be authorized to work in the U.S. This position is not eligible for sponsorship.

Job Description:
This role supports data-driven decision-making by bridging the product and data science functions within the team, translating broad datasets into actionable results.

Job Summary
•Analyze large and varied datasets to identify trends, patterns, and actionable insights for the organization.
•Develop and maintain data pipelines and queries using SQL and Snowflake to support team deliverables.
•Build and present clear data visualizations and reports using Power BI, PowerPoint, Word, and Excel.
•Write and maintain Python scripts to support data analysis and automation workflows.
•Collaborate closely with product and data science stakeholders to align on priorities and deliverables.
•Lead a small group of contributors on defined deliverables, driving ownership and accountability.
•Communicate findings clearly to both technical and non-technical audiences, driving results through data storytelling.

Minimum Requirements:
•Bachelor's degree in a STEM field.
•Proficiency in SQL with a solid understanding of querying and data manipulation.
•Hands-on experience with Snowflake.
•Proficiency in Python for data analysis or workflow automation.
•Strong communication skills with the ability to drive results and take ownership of work.
•Experience leading or coordinating a small team or group on project deliverables.
•Must be located in the valley (local candidates only).

Preferred Qualifications:
•Experience with Power BI for data visualization and reporting.
•Familiarity working across product and data science functions within a cross-functional team.
•Comfort working with broad, ambiguous datasets and narrowing focus to key outcomes.

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