Business Analyst

We are seeking a dynamic and results-oriented Business Analyst with expertise in Excel, SQL, Python and Power BI to join our team. The Business Analyst will be responsible for leveraging data analysis tools and techniques to extract insights, drive informed decision-making, and support business operations. The ideal candidate should possess strong analytical abilities, proficiency in Excel, SQL querying, Python and Power BI reporting, along with excellent communication skills.

Must Have skills:

1. SQL Intermediate to advanced level proficiency required

2. Excel Intermediate to advanced level proficiency required

3. Power BI - Intermediate to advanced level proficiency required

4. Python - Intermediate to advanced level proficiency required

5. Analytical Skills: Ability to analyze data, identify trends, and draw meaningful insights to support decision-making.

6. Communication Skills: Strong verbal and written communication skills to effectively convey complex ideas and requirements to stakeholders.

7. Problem-Solving Skills: Capacity to identify problems, evaluate options, and implement effective solutions.

Good to have skills:

1. PySpark

2. Databricks

3. Machine Learning and AI

Qualifications:

1. Bachelor's degree in Computer Science, Statistics, or a related field.

Key Responsibilities:

1. Utilize advanced Excel functionalities to manipulate and analyze large datasets, create reports, and generate actionable insights.

2. Write complex SQL queries to extract and analyze data from relational databases, ensuring data integrity and accuracy.

3. Develop interactive and visually compelling dashboards and reports using Power BI to present key performance indicators and trends.

4. Collaborate with team leads to understand business requirements and translate them into data-driven solutions.

5. Perform ad-hoc analysis to support business decisions, identify opportunities for process improvement, and optimize operational performance.

6. Conduct thorough data validation and reconciliation to ensure consistency and reliability of reporting metrics.

7. Proactively identify data discrepancies, anomalies, and trends, and recommend corrective actions as needed.

8. Provide training and support to end-users on data tools and techniques, empowering them to leverage data effectively.

9. Collaborate with cross-functional teams to streamline data processes, enhance data quality, and drive organizational efficiency.