Role : Data Analyst (Tableau)

Experience: 2 to 5 Years

Company: Yes Madam

Location: Noida

Working Days: 5.5 days; work from office

About Yes Madam:

Yes Madam is a leading at-home beauty, wellness, and salon services platform, focused on delivering convenience, quality, and exceptional customer experience. As we scale rapidly, customer and partner retention is a critical growth driver for us.

About the Role:

We are looking for a detail-oriented and analytical Data Analyst with strong Tableau expertise to transform complex data into actionable insights. The ideal candidate will be responsible for data analysis, dashboard creation, reporting automation, and supporting business decision-making through data-driven insights.

Key Responsibilities:

- Collect, clean, and analyze large datasets from multiple sources.

- Design, develop, and maintain interactive dashboards and reports using Tableau.

- Translate business requirements into analytical solutions and visualizations.

- Perform data validation, quality checks, and ensure data accuracy.

- Identify trends, patterns, and insights to support strategic decision-making.

- Collaborate with cross-functional teams including Product, Sales, Marketing, and Operations.

- Automate recurring reports and improve reporting efficiency.

- Present insights and recommendations to stakeholders in a clear and structured manner.

Required Skills & Qualifications:

- 2+ years of experience in data analysis or business intelligence roles.

- Strong hands-on experience with Tableau (dashboard creation, calculated fields, LOD expressions, data blending).

- Proficiency in SQL for data extraction and manipulation.

- Strong understanding of data modeling and data visualization best practices.

- Experience with Excel and/or Google Sheets.

- Basic understanding of statistics and data interpretation.

- Strong problem-solving and analytical skills.

- Excellent communication and presentation skills.

Good to Have:

- Experience with Python (Pandas, NumPy) or R.

- Knowledge of data warehousing concepts.

- Experience working with large datasets and cloud platforms (AWS, GCP, Azure).