Executive Data Analytics

Key Feature of The Role:

Reporting directly to the Manager, Data Analytics Executive supports key analytics projects, in charge of collecting, processing, and visualizing data to generate insights, driving data-informed decision-making. This role is responsible for ensuring the accuracy, consistency, and timeliness of data, as well as assisting in the maintenance of the organization's dashboards, reports and data pipelines. The role requires a strong grasp of data tools, a detail-oriented mindset, and effective communication skills to collaborate across teams.

Role Description:

1. Data Collection, Preparation & Validation

2. Collect, clean, and prepare data from multiple internal and external systems.

3. Conduct basic data validation and reconciliation to ensure completeness and accuracy.
4. Support integration of new data sources into existing datasets and reporting workflows.

5. Maintain documentation for data sources, tables, and transformation logic.

6. Analytics & Insights Support

7. Conduct exploratory and descriptive data analysis under supervision.

8. Assist in preparing analytical summaries, charts, and visualizations to support business reports and presentations.

9. Generate operational dashboards, performance metrics, and KPIs for regular reporting cycles.

10. Dashboarding & Reporting

11. Update and maintain dashboards and reports using Power Bi, Looker Studio, or Tableau.

12. Automate recurring reporting processes and contribute to data refresh scheduling.

13. Ensure dashboards are accurate, visually clear, and aligned with business requirements.

14. Cloud & Data Platform Support

15. Support in managing datasets within Google Cloud Platform (GCP) and BigQuery environment.

16. Run SQL queries and assist in data extraction, transformation, and loading (ETL) tasks.

17. Monitor scheduled data jobs, report anomalies, and assist in troubleshooting data issues.

18. Governance & Compliance

19. Ensure adherence to data governance standards, including privacy, accuracy, and version control.

20. Maintain secure handling of data and ensure compliance with organizational data policies.

21. Support the tracking of data usage, access, and quality metrics.

22. Collaboration & Learning

23. Support analytics projects and improvement initiatives.

24. Participate in internal knowledge-sharing, data training, and upskilling programs.

25. Contribute ideas to improve data processes, automation, and report efficiency.

26. Other Duties

27. Undertake any other duties or assignments as directed by the Management

Requirements:

1. Hold a Bachelor's degree in Data Science, Analytics, Statistics, Economics, Computer Science, or a related field. An advanced degree (MBA, MS in Data Science) is an advantage.
2. Professional certification (if any): Data-related certification is an added advantage
3. Minimum 3 years' experience in data analytics, business intelligence or a related field, with exposure to cross-functional collaboration and stakeholder engagement is desirable.
4. Proficiency in both written and spoken English and Bahasa Melayu.

Technical Skills:

• Proficiency in Microsoft Office. Advanced Excel skills (advanced formulas, power pivot) are added advantage
• Data Analysis & Visualization: Proficient in Power BI, Tableau, Looker Studio, Excel, and basic statistical tools to generate insights.
• SQL & Data Querying: Expert in writing and optimize queries to extract data from various databases.
• Data Management: Proficient in working with structured/unstructured data and maintaining data quality.
• Basic Python/R (Preferred): Competent with scripting for data analysis or automation.
• Reporting & Documentation: Competent in preparing clear and concise analysis reports.
• Project Management in Analytics - Proficient to lead end-to-end delivery of analytics projects including planning, coordination, execution, and impact evaluation.
• Exposure to any cloud platform (Azura,AWS, Google Cloud) is an advantage.

Soft Skills:

• Analytical & Problem-solving skills - Ability to anticipate risks, identify opportunities, and propose effective solutions
• Stakeholder Engagement & Communication - Strong interpersonal skills to engage with senior leadership, technical teams, and external partners, translating complex insights into clear narratives.
• Communication Skills - Excellent and professional communication with technical and non-technical users alike
• Adaptability & Innovation - Willingness to embrace change, learn new tools, and drive innovation through data.