Lead Data Architect

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.

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.

You'll be working with a team of Data Engineers, Data Scientists, and Data Analysts and 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.
• What You'll Do
• :
• Develop a deep understanding of the processes that make up our products and operations.
• Develop a deep familiarity of the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.
• Work effectively with the data, product, and business teams to gather and distill requirements that capture the reporting and analysis needs.
• Establish data modeling and naming standards to drive consistency across the data warehouse.
• Define and maintain the high-level data warehouse architecture including fact, dimension, and aggregation layers, the purpose of each, and the relationships between them.
• Collaborate with members of the data team to design the data models that allow us to measure the performance and comprehend the performance drivers for each of the processes that make up our complex business.
• Write, maintain, and communicate data design documentation.
• Oversee the implementation of data models.
• Develop, maintain, and manage the end to end data modeling process.
• Collaborate with our data engineering team to design our data pipeline infrastructure, abstractions, and tooling.
• Advocate data modeling depth, rigor, and consistency across the data and business teams. As well as coach data scientists and engineers into the principles of data modeling.
• What Are We Looking For
• Bachelor's degree in engineering, computer science, technology, or similar.
• 10+ years of overall experience working in data ideally with experience spanning multiple data disciplines e. g data science, data engineering, data analysis, and data warehousing.
• 5+ years of experience in data modeling at a high growth consumer product company or similar.
• Keen on a deep understanding of our business, product and operations. A piercing eye for important business questions that the data models would be able to answer. A drive for consistency, a mind for abstraction, and attention to detail.
• Experience with modeling diverse product and business processes, in particular:Modeling operational process data e. g. sales, delivery, and customer support to help us reason about capacity, utilization, efficiency, and quality.
• Modeling financial data to help us draw accurate pictures of our business health.
• Modeling user interactions with our products into user flows, funnels, and loops to help us measure user conversion and retention and to reason about the drivers of user drop-off and churn. A strong grasp on dimensional modeling concepts (e. g. fact table grain definition, logical views, dealing with non-additive facts, periodic and accumulating snapshots, changing dimensions, bridge tables, etc. ).
• Expertise in designing data pipelines (e. g. AirFlow DAGs) including the identification of dependencies, opportunities for abstraction, and performance bottlenecks.
• Experienced with running deep data investigations to answer business questions and with the creation of automated reports
• Deep familiarity with relevant technologies:For developing ETL pipelines (e. g. SQL and Python), For ETL orchestration (e. g. Airflow) ,For real-time distributed OLAP data-stores (e. g. Pinot or Druid), Familiarity with the Google Cloud Platform is a plus.
• How Do We Work?
• - In cross-functional squads - (Product Manager + Frontends + Backends + QA + Data Analyst),
• We do Code Reviews and are Clean Code practitioners
• We use Continuous Integration/Deployment
• We write all kinds of tests
• Business-oriented goals - the most important thing is what Tech Team delivers to the business at the end
• Technologies We Use
• - Frontend: JavaScript/ Ty