Data Warehouse Architect

Key Skills

AirByte, Apache Airflow, Apache Kafka, AWS Sagemaker, Big Data Technology, Confluence, Data Analysis, Data Biuld Tool - dbt, Data Modeling, Data Warehousing, Github, Google sheets, JIRA, Microsoft-Excel, PowerBI, Python Programming, Snowflake, SQL

Job Description

You’ll be working with a team (Kitopi) of Data Engineers, ML Engineers, 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.

You will:

• Own the data modeling standards and data models that make up our data warehouse.
• Lead the highly iterative dimensional modeling process.
• 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, in order to ensure a cohesive and effective data model.
• 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.
• 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.

Apply if you have:

• A Bachelor's or Master's degree in Engineering, Computer Science, Technology, or similar is required.
• 10+ years of experience working in data, with experience spanning multiple data disciplines, including 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.
• A willingness on gaining 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 are necessary traits for this role.
• Experience with modeling diverse product and business processes, including operational process data (e.g., Kitchen Operations, Logistics, and Supply chain), Growth data(Marketing, brands, sales and food menu), Customer experience(retention, contact center, feedback, ratings and reviews), Strategic data(market expansion, kitchen-brand fit), scrapping data(brand health and competition landscape), Subscription data(for our meal plans), user experience(for our dine-in and QSR), experimentation(for our product initiatives) and financial data.
• A strong grasp of dimensional modeling concepts, such as a fact table grain definition, logical views, dealing with non-additive facts, periodic and accumulating snapshots, changing dimensions, and bridge tables.
• Expertise in designing data pipelines (e.g., AirFlow DAGs), including identifying dependencies, opportunities for abstraction, and performance bottlenecks.
• Experienced with running deep data investigations to answer business questions and with creating automated reports.

You will be a perfect match for us if you have:

• Deep familiarity with relevant technologies below (nice to have)

Technologies We Use

• Data Warehouse / Big Data: Snowflake, ADL, and Postgres
• Reporting: Looker and Power BI
• Data Pipelines: Kafka, Python, SQL, Airflow, Airbyte, and DBTML
• Ops: Amazon SageMaker
• Platform: AWS
• Repository: GitHub
• Analysis: SQL, Python, and Excel
• Presentation: Power BI, Google Sheets, and Google Slides
• Documentation: Confluence
• Sprints and Backlog: Jira

Perks & Benefits:

• Expanded tech stack and no legacy code
• ESOP - Employee Stock Option Plan 
• You choose a form of employment (26 paid days off on B2B)
• Additional paid days off for volunteer activities
• Top-notch equipment: high-end MacBook Pro + additional accessories
• Support for your development: 2 000 PLN growth annual budget available to every employee, internal initiatives: webinars/workshops, knowledge sharing sessions internal conferences (Kitopi Academy)
• Mentoring program 
• Freedom Day - time for things you are passionate about
• Free English classes with a native speaker
• Worksmile benefit platform (private medical healthcare, Multisport card, vouchers, etc.) 
• Life insurance 
• Wellbeing program (psychological care, physical health, and socializing activities)
• Referral bonus 
• Flextime and Flexplace: adjust your daily schedule to your individual needs
• Great office with fruit & snacks, rented football pitch, social budget for every team & awaydays, and more!