Data Analyst

Responsibilities:

• Extract, clean, transform, and analyze large datasets to identify trends and business insights.
• Write complex SQL queries, including joins, subqueries, CTEs, window functions, and aggregations.
• Perform data manipulation and analysis using Python libraries such as Pandas and NumPy.
• Develop and maintain reports, dashboards, and automated reporting solutions.
• Work with Power Query for data transformation and data preparation.
• Use advanced Excel functions, pivot tables, lookup functions, and data analysis techniques.
• Collaborate with business stakeholders to understand requirements and deliver data-driven insights.
• Ensure data accuracy, consistency, and integrity across reports and datasets.
• Support business decision-making through analytical reports and actionable recommendations.

Requirements:

• Experience: 2-3 years.
• Key Skills: SQL (primary skill, must be strong), Python (Pandas, NumPy), Power Query, Advanced Excel, Power BI, and cloud exposure (Azure/AWS/GCP) are a plus.
• SQL: Strong hands-on experience in complex SQL queries, joins, CTEs, subqueries, and window functions.
• Python: Practical experience with Pandas and NumPy for data analysis and manipulation.
• Power Query: Experience in data extraction, transformation, and preparation.
• Advanced Excel: Strong knowledge of Pivot Tables, VLOOKUP/XLOOKUP, INDEX-MATCH, formulas, and data analysis.
• Data Visualization: Basic to good understanding of Power BI and dashboard development.

Good to Have:

• Exposure to cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).
• Experience working with large datasets and business intelligence tools.
• Understanding of data warehousing and ETL concepts.