Data Analyst II (Saudi National)

Hungerstation is part of the Delivery Hero Group, the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in around 65 countries worldwide. Headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. Job Description As a Data Analyst II at HungerStation, you will support the product development lifecycle by analyzing data, understanding user needs, and providing actionable insights that help optimize product performance. You will work closely with Product, Technology, Marketing, Commercial, Logistics/Operations, and Growth teams to turn data into meaningful insights and support data-driven decision-making. In This Role, You Will • Analyze product and business data to understand growth drivers and identify opportunities for improvement. • Develop analyses, reports, and interactive dashboards to support business teams and stakeholders. • Use quantitative analysis to uncover insights and help Product Managers, Designers, and Engineers understand what to build and why. • Work with structured and semi-structured data from multiple sources, including BigQuery, Redshift, and PostgreSQL. • Use SQL (BigQuery) and Python or R to extract, process, and analyze large datasets. • Design and analyze A/B tests by defining hypotheses, setting up experiments, and evaluating results using statistical methods. • Own data projects from data collection through to operationalization. • Build and maintain dashboards and reports using tools such as Looker Cloud, Tableau, Google Data Studio, or similar visualization platforms. • Contribute to continuous improvement of data and analytical processes. Qualifications • 2–4 years of relevant experience in Data Analytics or a related field. • Bachelor’s degree in Business Administration, Computer Science, Information Systems, or a relevant field. • Strong SQL skills, with experience using BigQuery. • Python or R experience is required. • Basic knowledge of statistics and experience applying statistical methods to data. • Experience working with large datasets and data from multiple sources. • Strong analytical and problem-solving skills. • Experience creating dashboards and reports using tools such as Looker Cloud, Tableau, Google Data Studio, or similar. • Ability to translate data into clear, actionable insights for business and product stakeholders. • Strong communication and collaboration skills, with the ability to work across Product, Technology, Marketing, Commercial, Logistics/Operations, and Growth teams.

2–4 years of relevant experience in Data Analytics or a related field. Bachelor’s degree in Business Administration, Computer Science, Information Systems, or a relevant field. Strong SQL skills, with experience using BigQuery. Python or R experience is required. Basic knowledge of statistics and experience applying statistical methods to data. Experience working with large datasets and data from multiple sources. Strong analytical and problem-solving skills. Experience creating dashboards and reports using tools such as Looker Cloud, Tableau, Google Data Studio, or similar. Ability to translate data into clear, actionable insights for business and product stakeholders. Strong communication and collaboration skills, with the ability to work across Product, Technology, Marketing, Commercial, Logistics/Operations, and Growth teams.

Analyze product and business data to understand growth drivers and identify opportunities for improvement. Develop analyses, reports, and interactive dashboards to support business teams and stakeholders. Use quantitative analysis to uncover insights and help Product Managers, Designers, and Engineers understand what to build and why. Work with structured and semi-structured data from multiple sources, including BigQuery, Redshift, and PostgreSQL. Use SQL (BigQuery) and Python or R to extract, process, and analyze large datasets. Design and analyze A/B tests by defining hypotheses, setting up experiments, and evaluating results using statistical methods. Own data projects from data collection through to operationalization. Build and maintain dashboards and reports using tools such as Looker Cloud, Tableau, Google Data Studio, or similar visualization platforms. Contribute to continuous improvement of data and analytical processes.