Data Architect

Fetcherr is an AI-driven company specializing in deep learning, algorithmic trading, and large-scale data solutions. Our core technology, the Large Market Model (LMM), enables accurate demand forecasting and real-time, data-driven decision-making. Originally focused on the airline industry, Fetcherr is expanding its AI solutions across additional industries.

We are seeking a Data Architect to define and develop the data architecture that powers our cloud-native platform, machine learning workflows, and decision-making processes. You will work closely with engineering, product, data science, and analytics teams to ensure our data platforms, models, and pipelines are scalable, reliable, and aligned with business needs. While product and engineering teams remain responsible for their own implementations, you will provide the architectural direction, standards, and cross-team guidance needed to keep our data ecosystem cohesive and future-ready.

Key Responsibilities

• Define and evolve the company’s data architecture to support scalability, reliability, governance, and long-term platform growth.
• Partner with engineering, data science, and analytics teams to ensure data pipelines, storage systems, and data models align with architectural standards and business goals.
• Establish best practices for data modeling, data integration, data quality, metadata management, and lifecycle design across teams.
• Design architectural frameworks that support machine learning use cases, including data ingestion, feature generation, training datasets, and model-serving dependencies.
• Participate in design reviews and provide guidance on data architecture patterns, trade-offs, and long-term maintainability.
• Help teams make sound decisions around data platforms, processing frameworks, orchestration, and storage technologies.
• Support agile squads early in the planning process to ensure data architecture considerations are incorporated from the start.
• Mentor technical leads and senior engineers on data architecture thinking and connect local decisions to broader technical strategy.
• Contribute to data governance and consistency by promoting secure, well-structured, and discoverable data systems.
  
  

• 10+ years of experience in software architecture or system design for large-scale, cloud-based applications.
• Deep experience designing systems that incorporate big data and machine learning workflows in a SaaS environment.
• Strong architectural knowledge of cloud infrastructure, ideally Google Cloud Platform; AWS or Azure experience is also welcome.
• Hands-on technical ability, with experience translating architectural direction into practical implementation decisions and supporting teams in execution.
• Experience with Apache Iceberg and modern data lake or lakehouse architectures.
• Experience with Dagster, Airflow, or similar orchestration tools.
• Experience with Ray or related distributed compute frameworks.
• Proven experience working within agile cross-functional teams, with the ability to drive architectural direction and technical outcomes without direct line management.
• Excellent communication and influencing skills, with the ability to balance technical vision with practical implementation.
• Passion for platform thinking, clean system design, and sustainable long-term architecture.
  
  

• Exposure to event-driven architecture or service mesh patterns.
• Advanced degree in Computer Science or a related field.
• Google Cloud Professional Architect or equivalent certification.