Data Analyst – Retail Performance & Business Intelligence (Mid-Level)

Position Overview
We are seeking a data-driven Retail Data Analyst to optimize omni-channel performance. In this role, you will analyze large datasets spanning in-store transactions, e-commerce behavior, and customer loyalty programs. Using Power BI and Python, you will build high-impact business dashboards, automate repetitive data preparation, and deliver insights to merchandising and marketing stakeholders.

Key Responsibilities

· Dashboard Development: Design and maintain interactive Power BI dashboards to track weekly/monthly store KPIs, sales velocity, and profit margins.

· Data Wrangling: Write clean Python scripts (using pandas and NumPy) to extract, clean, and merge messy data across point-of-sale (POS) systems, Shopify, or ERPs.

· DAX Modeling: Build relational data models and complex DAX measurements in Power BI Desktop to calculate customer lifetime value (LTV) and basket size metrics.

· Trend Analysis: Identify structural shifts in retail metrics like conversion rates, average order value (AOV), and promotional performance.

· Stakeholder Delivery: Present clear analytical findings and "data stories" to category managers to influence markdown and stocking decisions.

Required Skills & Qualifications

· Experience: 2–4 years of experience analyzing operational data, preferably within a retail or consumer goods environment.

· Power BI Mastery: High proficiency in Power BI, Power Query, and writing advanced DAX calculations.

· Python Capabilities: Hands-on experience writing Python scripts for ETL, data cleanup, and structural analysis.

Core Technical Stack: Strong SQL querying skills to extract information from cloud data warehouses (e.g., Snowflake, Azure SQL).

Benefits:

• Punctuality bonus
• Performance bonus
• Growth opportunities
• 15 Annual Leaves.
• Annual Leaves encashment
• Yearly increment
• Alternate Saturdays Off with encashment
• Paid Overtime
• A chance to work for US top-rated brands

Job Timings:
08:30 PM to 05:30 AM (Night Shift) - This may change due to Day-Light Saving

Application Question(s):

• Do you have experience working as a Data Analyst in the retail e-commerce business?
• Are you fine working on-site night shift?
• What's your Current/ last Salary?

Work Location: In person