[HCM] Data Analyst

POSITION OVERVIEW

As a Data Analyst or Analytics Engineer, you will collaborate with the Data Engineering team to transform large datasets into actionable insights, supporting data-driven decision-making across the organization. You will work closely with business teams to understand their needs and deliver tailored analytical solutions, including data analysis, visualization, and model building to drive strategy. Your work will leverage the infrastructure built by Data Engineering to create robust analytics systems that optimize our menu offerings, customer experience, operational efficiency, and marketing initiatives.

WHAT YOU WILL DO

• Data Analysis & Insights: Analyze large datasets to identify trends, patterns, and actionable insights that support business objectives and decision-making across restaurant operations, sales, marketing, and customer experience

• Collaborate with Business Teams: Work closely with business stakeholders to understand their challenges, define their analytical needs, and translate them into actionable data insights

• Data Modeling & Transformation: Design and implement data models that support reporting, analytics, and business intelligence requirements, in collaboration with the Data Engineering team

• Dashboard & Reporting: Design and develop automated dashboards and reports using BI tools to provide timely data visualization and insights for various business units

• Performance Monitoring & Optimization: Monitor and optimize the performance of analytical queries and dashboards, ensuring fast and reliable insights

• Data Quality & Security: Ensure data accuracy and consistency across different systems, implementing best practices for data governance and security

• Statistical Analysis: Perform statistical analyses to evaluate the effectiveness of marketing campaigns, menu changes, and operational improvements

• Forecasting & Prediction: Develop models to forecast sales, customer demand, and inventory requirements

• Support additional tasks or responsibilities as assigned by the line manager to contribute to the team‘s and organization‘s success

Example Projects

• Analyzing customer ordering patterns to optimize menu design and pricing strategies

• Creating interactive dashboards to monitor restaurant performance metrics across locations

• Developing demand forecasting models to improve inventory management and reduce waste

• Building cohort analysis models to understand customer retention and lifetime value

• Designing data models that enable self-service analytics for business users

1. Required Qualifications

• Bachelor‘s degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field

• Minimum 3 years of experience in Data Analysis or Analytics Engineering, with a proven ability to deliver actionable insights from large datasets

• Strong SQL skills and hands-on experience with the modern data stack on cloud platforms such as GCP, AWS, or Azure

• Experience with BI/visualization tools (e.g., Superset, Looker, Metabase), with deep expertise in designing and implementing interactive dashboards and comprehensive reports to deliver actionable insights

• Skilled in data analysis and transformation, with expertise in tools like dbt, Dataform, or equivalent, to design and refine data models that support analytical reporting and business intelligence

• Experience with at least one programming or scripting language (Python, R) for data manipulation and analysis

• Demonstrated ability to translate complex data findings into actionable business recommendations

• Solid understanding of data quality, security, and documentation best practices

• Strong problem-solving skills, attention to detail, and a self-learning attitude

• Proficient in English, both written and verbal, with the ability to read technical documentation and communicate effectively with cross-functional teams

2. Preferred Skills

• Experience in the restaurant, hospitality, or retail industry

• Knowledge of restaurant metrics and KPIs (food cost, table turnover, customer acquisition cost, etc.)

• Experience with A/B testing and experimental design

• Familiarity with statistical analysis methods and techniques

• Knowledge of dimensional data modeling and data warehouse concepts

• Experience with geospatial analysis for location-based insights

• Understanding of machine learning concepts and applications in business analytics

• Experience working with POS data, customer feedback systems, and inventory management platforms