Graduate Data Analyst / Junior Data Analyst / Data Analyst

Graduate Data Analyst / Junior Data Analyst / Data AnalystRole Description We are seeking a curious, analytical, and detail-oriented Graduate Data Analyst / Junior Data Analyst / Data Analyst to join our business intelligence and analytics team. In this entry-to-early-career role, you will play a key part in turning raw operational data into actionable insights, designing clear performance dashboards, and supporting business units with quantitative analysis. Working closely with Senior Data Analysts, Data Engineers, and Cross-Functional Leads, you will extract, clean, structure, and interpret datasets to help drive evidence-based decision-making across the organization. Responsibilities include querying corporate data warehouses, creating interactive visual reports, tracking key performance indicators (KPIs), investigating data discrepancies, and conducting ad-hoc exploratory analyses. Success in this position requires a strong quantitative mindset, solid proficiency in SQL and Excel, familiarity with modern data visualization platforms, high numerical accuracy, and the ability to articulate technical data findings clearly to non-technical stakeholders. Qualifications Education: Bachelor's degree or Diploma in Data Analytics, Computer Science, Statistics, Mathematics, Information Systems, Business Analytics, Economics, or a related quantitative discipline. SQL & Database Foundations: Practical knowledge of writing clean SQL queries (SELECT, JOIN, GROUP BY, WHERE, ORDER BY, aggregate functions, and basic subqueries) across relational databases (e.g., PostgreSQL, MySQL, BigQuery, SQL Server, or Snowflake). Data Visualization & Dashboarding: Hands-on experience or academic project work building reports and interactive dashboards using modern Business Intelligence tools (e.g., Power BI, Tableau, Looker Studio, or Qlik). Spreadsheet Proficiency: Strong working knowledge of Microsoft Excel or Google Sheets (XLOOKUP/VLOOKUP, Pivot Tables, SUMIFS, logical statements, and data formatting) for rapid data auditing and preliminary calculations. Data Cleansing & Structuring: Familiarity with data wrangling methodologies, handling missing values, identifying duplicate records, and structuring unstructured or raw datasets for reliable downstream reporting. Programming & Scripting Exposure (Bonus): Foundational exposure to Python (Pandas, NumPy, Matplotlib) or R for automated data cleaning, data manipulation, or exploratory data analysis (EDA). Statistical Fundamentals: Understanding of core descriptive statistics, variance, averages, distributions, probability, and metrics tracking to interpret trends accurately without misrepresenting data. Analytical Reasoning & Problem Solving: Strong diagnostic mindset with the ability to break down complex operational questions into structured analytical steps and investigate root causes behind trend shifts. Communication & Data Storytelling: Excellent written and verbal communication skills with an aptitude for presenting complex quantitative trends through intuitive visuals, concise bullet points, and actionable summaries. Professional Attributes: Meticulous attention to numerical detail, high curiosity, proactive eagerness to expand technical analytics skill sets, and a collaborative team-player mindset in fast-paced environments.