About the role
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.