Fetcherr experts in deep learning, algo, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.

As a Data Architect, you will play a key role in designing, optimizing, and scaling Fetcherr’s data architecture. You will work closely with our data engineers, data scientists, and AI teams to ensure efficient data storage, processing, and usage. This role is crucial in supporting Fetcherr’s mission to provide real-time, data-driven insights and recommendations to our airline partners.

Key Responsibilities:

• Design, implement, and maintain scalable and efficient data architecture for processing daily streams of data
• Optimize BigQuery usage to ensure high performance, efficiency, and cost-effectiveness
• Develop and implement strategies to meet the demands of scaling data and model training
• Collaborate with data engineering teams to ensure seamless ingestion and transformation of data streams into BigQuery
• Establish and enforce data governance policies to ensure data quality, security, and consistency
• Work closely with AI and data science teams to support model training and deployment
• Collaborate with DevOps and cloud teams to optimize storage and compute resources
• Act as a subject matter expert, providing guidance and mentorship to team members
• Identify and evaluate emerging data technologies to enhance Fetcherr's data architecture
• Implement solutions to scale data infrastructure for increasing data volumes
• Monitor and improve database performance and query efficiency
  
  

• At least 2 years of proven experience as a Data Architect in a data-intensive environment
• A hands-on approach with proven ability to implement solutions directly
• Strong expertise in BigQuery and other cloud-based data warehousing solutions (e.g., Snowflake)
• Deep understanding of database design, data modeling, and optimization techniques
• Experience with processing and managing large-scale data streams
• Proven ability to troubleshoot complex data performance and scalability issues
• Experience in balancing data architecture performance with cost efficiency
• Proficiency in SQL and Python (or another programming language for data processing)
• Familiarity with cloud platforms (preferably Google Cloud) and cost optimization strategies
• Strong analytical mindset with ability to design efficient, scalable data solutions
• Strong communication and collaboration skills
  
  

• Self-motivated with passion for solving challenging data problems
• Ability to work in a fast-paced, dynamic environment