Data Analyst

Responsibilities:

• Collect, clean, validate, and analyse large datasets from multiple sources.
• Write and optimise SQL queries to extract, manipulate, and analyse data.
• Develop interactive dashboards, reports, and visualisations using Power BI or Tableau.
• Perform exploratory data analysis to identify trends, patterns, anomalies, and business opportunities.
• Use Python or R for data manipulation, automation, and statistical analysis.
• Collaborate with business and technical stakeholders to understand data requirements.
• Define, monitor, and report key performance indicators (KPIs) and business metrics.
• Prepare regular reports and present actionable management insights.
• Identify data quality issues and implement processes to improve data accuracy and consistency.
• Automate repetitive reporting and data-processing tasks.
• Support forecasting, trend analysis, and business performance evaluation.
• Maintain proper documentation of data sources, analytical processes, and reporting methodologies.

Requirements:

• Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, Business Analytics, or a related field.
• 2-6 years of relevant experience in data analytics or business intelligence.
• Strong hands-on experience with SQL, Excel, and at least one visualisation tool.
• Ability to interpret complex datasets and communicate insights effectively.
• Strong attention to detail, problem-solving skills, and business understanding.
• Ability to work independently and collaborate with distributed teams in a remote environment.

Nice to Have:

• Data Analysis and Interpretation
• Advanced Microsoft Excel and Google Sheets
• SQL and Database Management
• Python or R Programming
• Data Visualization
• Power BI or Tableau
• Statistical Analysis
• Data Cleaning and Data Transformation
• Dashboard Development and Reporting
• Exploratory Data Analysis (EDA)
• KPI Tracking and Performance Reporting
• Analytical Thinking and Problem-Solving
• Business Intelligence (BI)

Good-to-Have Skills:

• Experience with cloud data platforms such as AWS, Azure, or GCP.
• Knowledge of ETL/ELT processes and data pipelines.
• Familiarity with BigQuery, Snowflake, or Databricks.
• Understanding of predictive analytics and forecasting.
• Experience with automation tools and data workflow optimisation.