Data Analyst

1. Extract financial, sales and operational data from relevant systems and approved data sources.
2. Validate source data to ensure accuracy, completeness, consistency and reliability before analysis.
3. Analyze and interpret complex datasets and transform them into meaningful business insights for Management decision-making.
4. Perform financial, sales and operational trend analyses to identify significant movements and performance patterns.
5. Identify data anomalies, exceptions, trends and unusual variances requiring further investigation.
6. Conduct analytical reviews across customers, products, branches, sales performance, costs and profitability.
7. Develop and maintain meaningful KPIs and performance indicators aligned with Management requirements.
8. Prepare analytical reports, dashboards and visualizations to communicate key findings clearly and effectively.
9. Perform data reconciliation and cross-check information between different systems and data sources where required.
10. Investigate significant variances and provide supporting analytical explanations and observations.
11. Support periodic forecasting, comparative analysis and performance monitoring.
12. Maintain proper analytical working files, data models and supporting documentation.
13. Ensure confidentiality, accuracy and integrity of financial and business information handled.
14. Independently evaluate analytical results before submission and minimize reporting errors.
15. Present and communicate key findings, trends, exceptions and business insights clearly to the Data Analysis Manager.
16. Assist the Data Analysis Manager in preparing Management reports, dashboards and decision-support analyses.
17. Perform other data analytical assignments and ad-hoc analyses as required by the Data Analysis Manager and Management.

Education and Skill Requirement

1. Bachelor's degree in Data Analytics, Data Science, Statistics, Computer Science, Information Systems, Finance, Accounting, Business Analytics or a related quantitative discipline.
2. Advanced Microsoft Excel – strong proficiency in advanced formulas, PivotTables, data analysis and large dataset handling.
3. Power Query – ability to extract, clean, transform, combine and prepare data from multiple sources.
4. Power BI – experience in developing interactive reports, management dashboards, KPIs and business intelligence visualisations.
5. DAX (Data Analysis Expressions) – ability to develop measures, calculated fields and analytical KPIs within Power BI.
6. SQL – ability to query, extract, manipulate and analyse data from databases.
7. Data Management & Modelling – strong knowledge of data cleansing, validation, reconciliation, transformation and data modelling.
8. Data Visualisation & Dashboard Development – ability to convert complex datasets into meaningful dashboards and management insights.
9. Financial & Sales Analytics – ability to perform trend and variance analysis covering financial performance, sales, customers, products, branches and profitability.
10. SAP S/4HANA Experience – Highly Preferred – practical exposure to SAP S/4HANA data, particularly: (DSD, FI, CO, MM & SD)
11. Additional Advantage – knowledge or practical experience in Python, statistical analysis, forecasting and analytical automation will be an added advantage.