Senior Data Analyst

• Gather data from multiple primary and secondary sources, ensuring accuracy and completeness.

• Perform data cleaning, transformation, and validation to prepare datasets for analysis.

• Assist in the development and maintenance of databases and data systems.

• Conduct statistical analysis and data mining to identify trends, patterns, and correlations.

• Support the development of analysis methodologies and techniques.

• Interpret data and analyze results using statistical and analytical approaches.

• Create and maintain regular and ad-hoc reports, dashboards, and visualizations.

• Present data clearly and effectively using charts, graphs, and tables.

• Ensure accuracy, clarity, and timeliness of reports delivered to stakeholders.

• Work with Marketing, Sales, Operations, and other teams to understand data needs.

• Provide analytical support and communicate findings to technical and non-technical audiences.

• Actively participate in team meetings and contribute to discussions on data use.

• Identify and resolve data discrepancies to maintain quality and integrity.

• Follow established data governance policies and procedures.

• Document data sources, methodologies, and processes for transparency and consistency.

• Stay up to date with industry trends, tools, and best practices in analytics.

• Continuously improve skills in data analysis tools and programming languages.

• Participate in training and development initiatives.

• Accurate, reliable, and timely reports and dashboards are consistently delivered to stakeholders.

• Data is cleaned, validated, and maintained to support high-quality analysis.

• Insights generated from analysis are used to inform marketing, sales, finance, and operations strategies.

• Collaboration with cross-functional teams leads to stronger data-driven decision making.

• Continuous improvements are made to data quality, documentation, and governance practices.

Qualifications

• Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, or a related quantitative field. Experience

• With 3-5 years experience in data analysis, data engineering, or business intelligence roles.

• Familiarity with SQL and database concepts.

• Exposure to data visualization tools (e.g., Tableau, Power BI, Superset). Skills and Competencies • Strong analytical and problem-solving skills.

• Basic programming knowledge in Python or R (preferred).

• Strong attention to detail and commitment to data accuracy.

• Ability to work independently and as part of a collaborative team.

Preferred Qualifications

• Knowledge of data warehousing concepts (e.g., Snowflake, BigQuery, Redshift).
• Experience in industries such as e-commerce, marketing, or finance is a plus.