Data Analyst - 1527

City: Kissimmee FL/ Remote

Onsite/ Hybrid/ Remote: Remote

Duration : 12 weeks

Rate Range : Up to$64/hr on W2 depending on experience (no C2C or 1099 or sub-contract)

Work Authorization : GC, USC, All valid EADs except OPT, CPT, H1B

Must Have:

• 3–5+ years of Data Analysis experience
  
• Strong proficiency in SQL and Excel (pivot tables, v-lookups, data modeling)
  
• Hands-on experience with at least one data visualization tool (Tableau, Power BI, or similar)
  
• Data aggregation and visualization project experience
  
• Prior experience as a Data Analyst for a retailer
  
• Understanding of product data

Responsibilities:

• Conduct detailed data analysis and ensure reporting accuracy across multiple jurisdictions.
  
• Develop and maintain dashboards, reports, and visualizations using BI tools (Tableau, Power BI, etc.).
  
• Acquire, filter, and clean large datasets from multiple sources to ensure data quality.
  
• Identify trends, patterns, and inconsistencies in datasets to drive insights.
  
• Partner with business stakeholders to gather requirements and deliver relevant reporting solutions.
  
• Support business intelligence capability development to improve reporting and decision-making.
  
• Communicate with international suppliers and internal teams to facilitate data collection and ensure compliance.
  
• Maintain thorough documentation of data projects, processes, and methodologies.

Qualifications:

• Bachelor’s degree in Data Analytics, Accounting, Finance, or related field.
  
• 3–5+ years of proven experience in data analysis, ideally in retail.
  
• Proficiency with SQL and Excel, including advanced functions and data modeling.
  
• Experience building visualizations and dashboards with BI tools such as Tableau or Power BI.
  
• Strong analytical mindset with attention to detail and accuracy.
  
• Ability to manage and interpret large datasets effectively.
  
• Strong communication, organizational, and problem-solving skills.
  
• Self-motivated, organized, and solution-oriented.
  

Preferred:

• Familiarity with Python or other data processing tools.
  
• Experience with packaging materials and retail product categorization.