Engineering · Full-time · Krakow, Poland
Kitopi is the world’s leading tech-powered multi-brand restaurant. With a mission to satisfy the world’s appetite, Kitopi operates a portfolio of both invested and franchised F&B brands, serving as enablers in the food market by helping brands to grow and scale, both in the delivery and dine-in space.
Launched in Dubai, UAE in January 2018, Kitopi has grown to become one of the greatest success stories in the cloud kitchen and food tech space. In July 2021, Kitopi announced its $415 million Series C funding round, led by the world’s largest technology-focused investment fund, Softbank Group Corp’s Vision Fund 2. This investment catapulted Kitopi to the prestigious Unicorn status, making it the fastest Unicorn to have emerged from the MENA region.
As a leading food-tech business, Kitopi’s growth has been largely fueled by its innovative and scalable software solutions. Kitopi’s kitchens are powered by its proprietary Smart Kitchen Operating System (SKOS) - an in-house suite of applications that optimizes cloud kitchen operations in real-time. As part of its growth roadmap, technological innovation, data science, artificial intelligence, and robotics will take center stage as Kitopi continues to reinvent the food industry as we know it today.
With over 4,000 employees, Kitopi currently operates 200+ locations across the UAE, KSA, Kuwait, Bahrain, and Qatar, and runs its engineering hub in Krakow, Poland, its robotics hub in Denmark, and its global customer experience center in Dubai, UAE.
At Kitopi, we are committed to empowering our business and product teams with robust reporting and analytics capabilities, enabling data-driven decision-making and fostering innovation. Collaborating closely with our product squads, we strive to leverage data-powered products to drive growth and enhance operational efficiency.
Within our structured data organization, comprising both business domain-focused verticals and technical practice-focused horizontals, we recognize the pivotal role of data modeling in elevating our reporting and analytics practices. You’ll be working with a team of Data Engineers, ML Engineers, and Data Analysts in collaboration with product and business managers across the company’s data ecosystem to design and continue to scale the data models that make up our data warehouse and support decision-making across our product and business.
Responsibilities:
In brief:
Set up the data modeling practice, processes and platform. Own the data models that make up our data warehouse.
Lead the highly iterative dimensional modeling process.
In detail:
Develop a comprehensive understanding of our products and operations and become intimately familiar with the source data and its generating systems, using a combination of documentation, direct interaction with engineering teams, and systematic data profiling.
Collaborate with the data, product, and business teams to gather and distill their reporting and analysis requirements and work together to design effective data models that accurately represent the underlying business processes.
Establish data modeling and naming standards that promote consistency and best practices across the data warehouse and communicate these standards effectively to the broader data team.
Define and maintain a high-level data warehouse architecture, including fact, dimension, and aggregation layers, and the relationships between them.
Work with members of the data team to design data models that effectively measure performance and capture the performance drivers for the various business processes in our complex business.
Write, maintain, and communicate data design documentation to ensure that the broader data team has a clear understanding of our data models and how they work.
Oversee the implementation of data models, ensuring that they are accurate, efficient, and scalable, and that they meet the reporting and analysis needs of the broader organization.
Develop, maintain, and manage the end-to-end data modeling process, from requirements gathering to model design to implementation and ongoing maintenance.
Collaborate with the data engineering team to design effective data pipeline infrastructure, abstractions, and tooling that support our data modeling efforts.
Collaborate with cross-functional teams to understand specific analytics requirements and create standardized data models that empower end-users to independently generate insights through self-service analytics tools.
Advocate for data modeling depth, rigor, and consistency across the data and business teams, and coach data scientists and engineers on the principles of effective data modeling.
Requirements:
Technologies We Use:
Perks & Benefits:
Open roles at Kitopi