Business Intelligence & Data Analytics – Senior Executive
Salary: RM 4,700 – RM 7,000 per month
About the Role:
Responsible for developing business intelligence solutions and transforming complex data into actionable business insights. Beyond technical capabilities, we are looking for someone who understands how businesses operate, can identify the commercial implications behind the numbers, and proactively recommends improvements.
This position will work closely with the MIS, Revenue, Marketing, Demand Planning, Production Planning, Supply Chain and Operations teams.
Key Responsibilities
1. Business Intelligence & Data Analytics
Develop, maintain and enhance interactive dashboards, analytical reports and data visualisations using Power BI and other relevant BI tools.
Analyse business performance across retail outlets, sales channels, customer segments, product categories and individual SKUs.
Conduct sales, revenue, profitability, margin, promotion and customer behaviour analyses to identify trends, opportunities and areas for improvement.
Monitor key business performance indicators (KPIs), identify unusual trends or performance deviations, and provide timely insights to relevant stakeholders.
Translate complex datasets into meaningful business insights, highlighting underlying causes, commercial implications and recommended actions.
Automate recurring reports and analytical processes to improve reporting efficiency, consistency and accuracy.
Collaborate with Demand & Supply Planning team to build the reporting dashboards and underlying data models necessary to support their forecasting, inventory, and operational decision-making
2. Data Management & Reporting Infrastructure
Collaborate with MIS to ensure business requirements are accurately reflected in the data warehouse models and consolidation efforts from multiple systems (ERP, POS, inventory).
Utilize advanced SQL and Power Query to extract, transform, and load prepared data into reporting-ready datasets.
Support the standardization of master data, business definitions, and reporting structures across departments and business entities.
3. Business Performance & Commercial Analytics
Work closely with Revenue, Marketing and Operations teams to evaluate sales performance, promotional effectiveness and customer purchasing behaviour.
Track product profitability, sales margins, SKU performance, and store-level business performance, alerting leadership when margins deviate from expectations.
Support the evaluation of new products, promotions, marketing campaigns and business initiatives through data-driven performance analysis.
4. Business Understanding & Stakeholder Collaboration
Develop a strong understanding of the company's end-to-end business processes, from sourcing and production to distribution and retail sales.
Engage with business users to understand operational challenges, reporting requirements and underlying business objectives.
Translate business requirements into practical data solutions, analytical models and management reports.
Demonstrate commercial awareness by interpreting not only what the data shows, but also why it matters and what actions should be considered.
Present analytical findings clearly to both technical and non-technical stakeholders.
Proactively recommend improvements to business processes, data structures and analytical capabilities.
Job Requirements
Education & Experience
Bachelor's Degree in Data Analytics, Computer Science, Information Systems, Business Analytics, Statistics, Mathematics, Finance or a related discipline.
Preferably 3–5 years of relevant working experience in Business Intelligence, Data Analytics, Data Engineering or related functions.
Experience in integrated supply chain, FMCG, food production, manufacturing or retail industries will be an added advantage.
Experience working with ERP, POS, inventory management, manufacturing or warehouse management systems is advantageous.
Technical Skills (Strong proficiency in the following areas is highly preferred):
SQL: Strong SQL querying skills, including complex joins, CTEs, stored procedures, query optimisation and data manipulation. Experience with Microsoft SQL Server is an advantage.
Python: Ability to use Python for data extraction, cleansing, transformation, automation and analytical processing.
Power BI: Experience developing interactive dashboards, data models, DAX measures and management reporting solutions.
Power Query: Strong knowledge of data transformation, data preparation and integration from multiple data sources.
Data Warehousing: Working knowledge of data warehouse architecture, relational databases, dimensional modelling and ETL/ELT processes.
Data Integration: Familiarity with APIs, database connectivity, system integrations and automated data pipelines.
Microsoft Excel: Advanced proficiency in Excel, including data analysis, complex formulas and data modelling.
Experience with cloud data platforms, Microsoft Fabric, Azure Data Factory, Microsoft SQL Server Integration Services (SSIS) or similar technologies will be an added advantage.
Business & Analytical Competencies
Strong analytical, numerical and logical problem-solving abilities.
Good business acumen with the ability to connect data findings to commercial and operational implications.
Ability to understand business workflows and translate business challenges into practical analytical solutions.
Proactive and inquisitive, with the ability to investigate underlying causes rather than simply reporting figures.
Strong attention to detail, particularly in data accuracy, validation and reporting consistency.
Good communication and presentation skills, with the ability to explain technical findings to business stakeholders.
Able to work independently while collaborating effectively with cross-functional teams.
Willingness to continuously learn and adopt new data technologies, analytical tools and business practices.
What We Are Looking For
We are looking for someone who can connect technology, data and business understanding.
An ideal candidate should not simply produce dashboards or reports, but should be able to:
Understand the business processes behind the data.
Identify trends, anomalies and underlying business issues.
Develop reliable data structures and analytical solutions.
Translate findings into practical recommendations.
Support management and operational teams in making better-informed decisions.
Our objective is not just to generate more reports, but to turn data into insights that drive measurable business improvements.