Data Architect

Our client, one of the world’s largest technology distributors, is looking for a Data Solution Architect to take ownership of an established enterprise data platform.

The Customer Data Platform, lakehouse and analytics ecosystem are already running in production. Your role will be to keep the architecture coherent, improve what is already in place and prepare the data platform for new AI use cases.

Data architecture is the core of this position. AI integration is a growing part of the role, and you’ll develop in this area alongside an experienced AI engineering team.

What makes the role interesting

• An enterprise platform combining hundreds of internal and external data sources.
• Billions of data points across millions of contacts, partners and end customers.
• A mature lakehouse based on Snowflake and Databricks.
• More than 80 AI/ML models already running in production.
• Real business use cases in sales, marketing, pricing, e-commerce and process automation.
• An international European Data Practice team of around 35 people from 9 nationalities.

What you’ll do

• Own and develop the architecture and roadmap of the enterprise data platform.
• Improve data ingestion, processing, storage and serving layers.
• Set architecture standards for data integration, modeling and governance.
• Work with medallion architecture, schema contracts, feature stores and semantic layers.
• Cover access control, security and compliance, including Unity Catalog, RBAC, data classification and GDPR.
• Improve CI/CD, monitoring, observability and platform cost management.
• Review solution designs and guide data engineers during implementation.
• Prototype critical components when a hands-on validation is needed.
• Translate business needs into technical specifications and delivery plans.

Your connection to AI

The dedicated AI engineering team owns models, agents and their internals. Your task will be to make sure the data platform gives them a reliable foundation.

You’ll gradually work on:

• Making governed and well-documented data available for AI applications.
• Designing APIs, serving layers, access patterns and data freshness standards.
• Extending data security and governance to AI use cases.
• Supporting the integration of AI applications with the data platform and enterprise APIs.
• Contributing to architecture decisions where AI and the data platform meet.

Previous hands-on AI architecture experience is welcome, but it isn’t required.

What we’re looking for

• Solid experience in data engineering or platform engineering.
• Previous experience as a Data Architect, Solution Architect or in a similar role.
• Strong knowledge of lakehouse architecture, ideally Snowflake and Databricks.
• Advanced Python and SQL.
• Strong knowledge of ETL/ELT, data integration and data modeling.
• Experience with enterprise, analytical or semantic data models.
• Understanding of data platform security, access control, encryption and compliance.
• Ability to explain complex technical decisions clearly to engineers and business stakeholders.
• Genuine interest in AI and willingness to grow into AI integration architecture.
• Advanced English for daily international cooperation.

Experience with Azure, Spark, Azure DevOps, event-driven architecture, API management, data mesh or MLflow will be an advantage.

Technology stack

Core: Snowflake, Databricks, Spark, Python, SQL, Azure, Azure DevOps, Unity Catalog, CI/CD and enterprise data modeling.

AI-related: MLflow, Agentic AI, LangChain, LlamaIndex and vector databases. Awareness is enough to start; the AI team handles model internals.

What they offer

• Ownership of enterprise data architecture in a global Fortune 500 company
• A clear growth path towards enterprise AI architecture
• Influence on the technology roadmap and future use of AI
• Large-scale platforms with real business impact
• An experienced international data and AI team
• Stable global environment with a practical, hands-on culture
• Hybrid setup: 3 days in the office and 2 days remotely
• Office in Prague 4 – Opatov
• The client also operates its own AI Labs, where real AI scenarios are tested across technologies from leading global vendors. This helps move new solutions into practice faster and with greater impact.
• 25 days of annual leave
• 2 fully paid sick days
• Hybrid working model (2 home-office days per week)
• Meal allowance
• Multisport card contribution
• Pension contribution
• Well-being days
• Accident insurance
• Mobile phone allowance and unlimited mobile plan
• Employee discounts on technology products