Senior Data Analyst
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Key Responsibilities
• Analyze, validate, and interpret large datasets from multiple business sources to generate meaningful insights and support data-driven decision-making.
• Develop, optimize, and maintain SQL queries, stored procedures, and data models to support reporting and analytical requirements.
• Design, develop, and maintain dashboards and reports using BI tools such as Power BI, Tableau, or similar reporting platforms.
• Perform data quality analysis, data validation, and root cause analysis to ensure data accuracy, consistency, and integrity.
• Collaborate with business stakeholders, data engineers, and cross-functional teams to gather requirements and translate them into analytical solutions.
• Support data warehouse initiatives, including data mapping, ETL validation, dimensional modeling, and data reconciliation.
• Conduct data investigations, trend analysis, and performance reporting to address complex business queries and operational challenges.
• Identify opportunities for process improvements, automation, and reporting optimization. Required Skills & Experience
• Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, or a related field.
• 2-9 years of experience in Data Analysis, Business Intelligence, Reporting, or Data Warehousing environments.
• Strong hands-on experience in SQL (queries, joins, stored procedures, performance tuning, data analysis).
• Experience with BI/Reporting tools such as Power BI, Tableau, QlikView, or similar platforms.
• Good understanding of Data Warehouse concepts, ETL processes, dimensional modeling, fact and dimension tables, and data lifecycle management.
• Strong analytical, problem-solving, and data interpretation skills.
• Experience working with relational databases such as Oracle, SQL Server, PostgreSQL, MySQL, or similar platforms.
• Knowledge of data governance, data quality, and data validation practices.
• Ability to communicate complex analytical findings effectively to technical and business stakeholders.
• Experience in financial services, investment data, ESG data, or enterprise analytics environments is an added advantage. Preferred Skills
• Exposure to PL/SQL, Python, or data automation tools.
• Understanding of cloud-based data platforms such as Azure, AWS, or Google Cloud.
• Experience working in Agile environments and collaborating with global teams.
• Strong stakeholder management and communication skills.
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