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Marketing Data Analyst

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Remote

Marketing Data Analyst

Private Advertiser

Marketing Data Analyst

Skills

SQL QueriesLookerE-commerce WebsitesTableauData VisualizationData AnalysisCommunication CampaignCRMGoogle AnalyticsGDPRProcess ImprovementPower BI

1 month ago

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Important information


Contract type:

Permanent

Salary:

MYR 48,000 – MYR 72,000 / year

Location:

Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Work mode:

Remote

Published on:

17 September 2026

What they need


Marketing Data Analyst

Location: Penang, Malaysia
Employment Type: Full-time

About the Role

We are looking for a detail-oriented Marketing Data Analyst to support marketing decisions through campaign analysis, customer insights, and business reporting.

You will analyse marketing performance across multiple products and markets, develop reports and dashboards, and translate complex data into practical recommendations. Working closely with internal teams, you will help identify opportunities to improve customer acquisition, engagement, retention, and marketing effectiveness.

Key Responsibilities

1. Marketing Performance Analysis

  • Analyse marketing campaign performance across different products, channels, and markets.
  • Track key marketing metrics, including customer acquisition, engagement, retention, conversion rates, cost per acquisition, and return on investment.
  • Compare campaign results against agreed targets, historical performance, and relevant benchmarks.
  • Identify performance trends, unusual movements, and areas requiring further investigation.
  • Evaluate which campaigns, channels, and customer segments contribute most effectively to business objectives.
  • Provide recommendations to support campaign optimisation and marketing budget allocation.

2. Business Intelligence & Reporting

  • Prepare daily, weekly, and monthly marketing reports according to business requirements.
  • Develop and maintain dashboards that present campaign results and business performance clearly.
  • Monitor agreed business metrics and highlight significant changes to relevant stakeholders.
  • Consolidate information from different data sources to support consistent reporting.
  • Present findings in a clear, structured manner for both technical and non-technical audiences.
  • Improve reporting templates and processes to reduce repetitive manual work.

3. Customer & Product Data Analysis

  • Analyse customer behaviour, product usage, and customer segments to identify meaningful patterns.
  • Review the customer journey to understand acquisition sources, conversion barriers, and retention opportunities.
  • Compare customer groups and markets to identify differences in engagement and campaign response.
  • Support campaign reviews through detailed analysis of results and contributing factors.
  • Investigate business questions raised by stakeholders and communicate findings with supporting evidence.
  • Identify opportunities for improvement while clearly explaining data limitations and analytical assumptions.

4. Cross-functional Collaboration

  • Work closely with Marketing, CRM, Product, Operations, and Finance teams to understand reporting and analytical needs.
  • Support campaign planning with insights from previous results and customer behaviour.
  • Coordinate with relevant teams to clarify data definitions, reporting requirements, and measurement methods.
  • Help stakeholders establish measurable campaign objectives and appropriate performance indicators.
  • Communicate analytical progress, findings, and outstanding data issues promptly.
  • Follow up on recommendations and assess their impact where sufficient data is available.

5. Data Quality & Process Improvement

  • Check data accuracy, completeness, and consistency before publishing reports.
  • Investigate discrepancies and coordinate with the relevant teams to resolve them.
  • Maintain documentation of key metrics, calculation methods, and reporting assumptions.
  • Identify opportunities to improve data preparation, dashboard maintenance, and reporting efficiency.
  • Handle business and customer information in accordance with company confidentiality and data protection procedures.

Requirements

  • Bachelor’s Degree in Marketing, Business Analytics, Statistics, Mathematics, Computer Science, or a related field.
  • Minimum 2 years of experience in Marketing Analytics, Business Intelligence, Data Analysis, or a related analytical role.
  • Strong Microsoft Excel skills, including Pivot Tables, XLOOKUP, Power Query, and SUMIFS.
  • Working knowledge of SQL for extracting, combining, and analysing data.
  • Experience with Power BI, Tableau, or Looker Studio is an added advantage.
  • Good understanding of marketing metrics and campaign performance measurement.
  • Strong analytical thinking, attention to detail, and problem-solving skills.
  • Ability to interpret data and translate findings into practical business recommendations.
  • Good communication and presentation skills, with the ability to explain results clearly.
  • Ability to manage multiple reporting requests and meet agreed deadlines.
  • Experience analysing digital platforms, FinTech services, E-commerce, or digital marketing campaigns is an added advantage.

Preferred Skills

  • SQL querying and data preparation.
  • Dashboard development using Power BI, Tableau, or Looker Studio.
  • Google Analytics 4 (GA4).
  • Marketing KPI analysis and conversion funnel reporting.
  • Customer segmentation and cohort analysis.
  • Understanding of A/B testing and campaign measurement.
  • Reporting automation and data visualisation.

Key Performance Indicators (KPIs)

  • Accuracy and consistency of reports and analytical outputs.
  • Timely delivery of scheduled reports and agreed analytical projects.
  • Reliability and usability of dashboards.
  • Quality and relevance of insights provided to stakeholders.
  • Timely identification and escalation of data discrepancies or performance changes.
  • Contribution of analytical recommendations to measurable campaign improvements.
  • Effective collaboration with internal teams.
  • Improvements in reporting efficiency and reduction of manual processing.

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