Data Project Manager

sodexo services asia pte. ltd.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Sodexo Services Asia Pte. Ltd. is seeking a data analytics professional to consolidate data from multiple sources into unified reports. You will forecast trends, generate actionable recommendations, and deliver insights to senior stakeholders.

The role emphasizes data collection, processing, and visualization using Google Sheets, Data Studio, BigQuery, and Power BI, with responsibilities spanning databases, dashboards, and reports for efficient operations.

Qualifications

• Proven experience in data analytics, preferably in the food services or hospitality industry.
• Proficiency in tools like SmartQ, Drive, and Lean Path (or similar systems).
• Strong skills in Google BI tools i.e. Data Studio, BigQuery and Google Sheets.
• Ability to analyze complex datasets and deliver actionable insights.
• Familiarity with demand forecasting, procurement trends, and waste management metrics.

Responsibilities

• Data Integration and Reporting: Develop a unified analytics framework to consolidate data from multiple sources into a single report.
• Data Collection and Processing: Gather data from databases, Excel, and Google Sheets; clean and validate data.
• Data Analysis: Analyze data using statistical techniques to identify trends and insights with SQL, Python or Excel.
• Data Visualization: Create dashboards with Data Studio and Power BI; present findings to stakeholders.
• Database Management: Design, maintain, and optimize databases; ensure data integrity and security.
• Reporting: Prepare detailed reports and summaries for business leaders with actionable recommendations.

Skills

Data analytics

Forecasting

Data visualization

Stakeholder collaboration

Tools

Power BI

Data Studio

Google Sheets

BigQuery

SQL

Python

Excel

Job description

Within this role you will report directly to Regional Account Director and work with Sodexo country teams and along with regional account team, your key responsibilities will include but not be limited to:

General

• Proven experience in data analytics, preferably in the food services or hospitality industry.
• Proficiency in tools like SmartQ, Drive, and Lean Path (or similar systems).
• Strong skills in Google BI tools i.e. Data Studio, BigQuery and Google Sheets.
• Ability to analyze complex datasets and deliver actionable insights.
• Familiarity with demand forecasting, procurement trends, and waste management metrics.

Key Objectives

Data Integration and Reporting:

• Develop a unified analytics framework to consolidate data from multiple sources into a single report.
• Generate site-specific trends, forecasts, and actionable recommendations to improve operational efficiency. Detailed description as per below:

Data Collection and Processing:

• Gather data from various sources such as databases, Excel spreadsheets, Google sheets.
• Clean and validate data to ensure accuracy and completeness.

Data Analysis:

• Analyze data using statistical techniques to identify trends, patterns, and insights.
• Use tools like Google sheets and SQL or Excel or Python for data manipulation and analysis.

Data Visualization:

• Create visualizations and dashboards using tools like Data Studio and Power BI to present data insights clearly.
• Develop reports and presentations to communicate findings to stakeholders.

Database Management:

• Design, maintain, and optimize databases and data systems.
• Ensure data integrity and security.

Reporting:

• Prepare detailed reports and summaries of data analysis for business leaders.
• Provide actionable recommendations based on data insights.

Technical and BI Tools Expertise:

• Experience with data visualization tools (e.g., Power BI and Data Studio).
• Knowledge of database management and data warehousing.
• Work with advanced Business Intelligence (BI) tools to develop dashboards, visualizations, and reports for stakeholders.
• Recommend and implement BI solutions to support long-term operational goals.

Stakeholder Collaboration:

• Work with cross-functional teams, including engineers, product managers, and business analysts, to understand data needs and provide insights.
• Collaborate with IT to implement data collection systems and other strategies that optimize statistical efficiency and quality.
• Engage with internal teams and external partners to understand business needs and align analytics with organizational goals.
• Train team members on data tools and analytics best practices as needed.