Compunnel Inc.

SQL Analyst

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an SQL Analyst with a contract length of "Unknown," offering a pay rate of "Unknown" and requiring remote work. Candidates must have 3+ years in retail analytics, intermediate SQL skills, and a relevant bachelor's degree.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
December 12, 2025
πŸ•’ - Duration
Unknown
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🏝️ - Location
Unknown
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Kissimmee, FL
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🧠 - Skills detailed
#BigQuery #NumPy #Data Analysis #Data Warehouse #Pandas #Matplotlib #Scala #A/B Testing #Automation #Snowflake #Datasets #Data Science #Python #"ETL (Extract #Transform #Load)" #SQL (Structured Query Language) #Storage #Cloud #AI (Artificial Intelligence) #Visualization #Mathematics #Tableau #Data Management #Redshift #BI (Business Intelligence) #Computer Science #Storytelling
Role description
Job Title -- MAZDC5697389 Sales Executive -- Anindya Mazumdar Must-Haves: Looking for an emphasis on soft line retails, (e.g., shirts). β€’ β€’ More experience on the Retail side is what's needed here. Ultimately it is a blended role (Retail & Analytics) but the Retail piece is KEY. Ideally want those with more Analytics than Retail Minimum 3 years analytical experience in retail, especially applying insights to business KPIs and decision-making. Intermediate SQL skills (3 years): data discovery, understanding storage, and data retrieval. Minimum 3 years Retail industry experience (KPIs, etc.) Nice-to-Haves: Tableau or other data visualization tools and building of dashboards for them Experience with pricing analytics (60% of the role). Familiarity with Snowflake, BigQuery, Redshift. Coding / technical aptitude in Python, and for data analysis purposes (using pandas, NumPy, matplotlib) Ability to support data preparation and light modeling tasks. Business Intelligence background A/B testing concepts and basic statistical techniques Bachelor’s degree in Mathematics, Economics, Data Science/Analytics, Computer Science, Operations Research, or a related field Future Skill Growth Opportunities: AI chatbot efficiency for operations Automation for Salesforce/Snowflake releases Business process analysis / technical requirements Resume-building with AI-related projects Responsibilities: Technical Business Acumen - Strong understanding of retail KPIs and operations with the ability to translate data into meaningful business recommendations that drive revenue, efficiency, or guest satisfaction. Retail Analytics - Experience supporting the business including merchandising, buying, planning, operations, marking, etc. in retail environments across brick-and-mortar and ecommerce channels. Familiarity with retail inventory systems, POS data, and product lifecycle metrics. SQL & Data Management - Advanced SQL skills to extract, join, and transform large datasets; experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift. Dashboarding & Data Visualization - Expert-level experience building dashboards and reports in Tableau or similar tools to drive self-service analytics and business storytelling. Functional Deliver Actionable Business Insights: Conduct deep-dive analyses on retail performance including pricing and promotional effectiveness, customer behavior, and product lifecycle to inform merchandising and planning decisions. Build and Maintain Visual Dashboards: Develop intuitive, automated Tableau dashboards and self-service reporting tools to monitor key performance indicators and support cross-functional teams in decision-making. Collaborate with Cross-Functional Teams: Partner with merchandising, marketing, finance, and technology stakeholders to translate business needs into data-driven solutions and clearly communicate analytical findings. Develop Scalable Analytical Solutions: Write robust SQL code to query, clean, and manipulate large datasets from cloud-based sources (e.g., Snowflake, BigQuery) in support of repeatable, scalable analytics workflows. Support Data Science Initiatives: Collaborate with data scientists on advanced projects by preparing data inputs, conducting exploratory data analysis, and validating model outputs to ensure business relevance