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Praha, Česko
Hybrid
Data (& AI) Solution Architect
TD SYNNEX is looking for a Data Solution Architect to own, evolve and scale our established enterprise data platform.
Our CDP, lakehouse, and analytics capabilities are mature and production-grade. This role is about architectural coherence, optimizing what’s running, and preparing the data estate for AI-driven use cases. Data and platform architecture is the core of this role; AI integration is a growing area you will grow into with us.
About the team
You will join our European Data Practice – Center of Excellence, a multidisciplinary team of ~35 experts across 9 nationalities, with backgrounds in telecom, banking, insurance, life sciences, and physics.
What we do
Enterprise data platform consolidating hundreds of data sources, processing billions of data points across millions of contacts, partners and end customers.
Modular lakehouse (Snowflake + Databricks) with medallion-based governance, feature stores, and semantic layers.
AI/ML modeling hub with 80+ production models: propensity scoring, recommender systems, churn prediction, Next Best Action.
Agentic AI systems (RAG/CAG, LLM-powered agents) — an emerging area owned by our dedicated AI engineering team.
Omni-channel orchestration and E2E process automation across ERP, CRM, e-commerce, and partner systems.
Your role
Data & Platform Architecture — your primary focus
Own and evolve the data platform architecture, blueprints, and roadmap across the CDP ecosystem.
Optimize ingestion, processing, storage, and serving layers for throughput, cost-efficiency, and governance.
Maintain medallion-based governance with schema contracts; evolve integration patterns for hundreds of sources.
Govern access control, security, and compliance: Unity Catalog, row-level security, data classification, encryption.
Drive platform maturity (CI/CD, observability, cost management) and conduct design reviews.
AI Enablement & Integration — a growing part of the role
Our AI engineering team owns models, agents, and their internals. Prior hands-on AI architecture experience is welcome but not a prerequisite.
Make enterprise data consumable by AI use cases — governed, trusted, well-documented data products.
Design the data-side interfaces AI applications rely on: APIs, serving layers, access patterns, freshness.
Extend existing governance and security to AI consumption: PII handling, data leakage prevention, audit trails.
Partner with AI engineers on technology selection where it touches the data platform.
Hands-on & Engineering Leadership
Decompose architectural decisions into well-scoped work items; mentor and review during implementation.
Prototype critical components hands-on and translate business requirements into technical specifications.
Required experience
Solid experience in data engineering / platform engineering, with a proven track record as Solution or Data Architect on enterprise-scale platforms.
Strong background in lakehouse architectures (Snowflake, Databricks).
Advanced Python, expert SQL and data modeling (dimensional, analytical, semantic).
Deep knowledge of ETL/ELT and enterprise data integration patterns.
Solid grasp of data platform security: access control, encryption, data classification, GDPR.
Strong communication skills; proactive, detail-oriented, sharp problem-solving.
Genuine interest in AI and willingness to grow into AI integration architecture.
Technology stack
Core: Snowflake, Spark / Databricks, Unity Catalog, Python, SQL, data modeling, Azure DevOps & CI/CD, Azure AD / RBAC, ERP / CRM / E-Commerce integrations, Azure (AWS or GCP a plus)
AI-adjacent (awareness is enough): Production AI workflows and MLflow, agent orchestration concepts, LangChain / LlamaIndex, vector DBs — all a plus, not a requirement
Nice to have
Hands-on experience integrating AI/ML into enterprise application and data architectures.
Practical exposure to Agentic AI: orchestration, tool use, API integration, governance.
Cloud or security certifications (AZ-305, Databricks Certified Architect, SC-100, AZ-500).
Event streaming (Kafka, Azure Event Hub), API management, or data mesh / data product thinking.
MLOps frameworks (MLflow, Kubeflow, Airflow); BSc/MSc/PhD in Computer Science, AI, or a related STEM field.
We can offer
Ownership of enterprise data architecture across a Fortune 500 organization.
A growth path into enterprise AI architecture, supported by an experienced AI engineering team.
Influence on technology strategy, platform roadmap, and AI adoption, with high leadership visibility.
A team of enthusiastic data professionals (who happen to love board games).
Stable environment with startup-like dynamics and an agile, experimental way of working.
Hybrid working mode (3 days in the office / 2 days remotely).
About the company
As a Fortune 500 global corporation, operating in over 100 countries, TD SYNNEX values its diverse workforce of 22,000 employees (about the seating capacity of Madison Square Garden). As the biggest IT distributor in the world, our mission is to provide top-notch technological solutions, empowering businesses and individuals to navigate the digital world safely and efficiently.
At TD SYNNEX, our values guide everything we do: Together, We Own It, We Dare to Go, We Grow and Win, and above all, We Do the Right Thing. These principles shape how we work with each other, our partners, and our communities as we drive innovation and create lasting impact.
What’s In It For You?
Don’t meet every single requirement? Apply anyway.
At TD SYNNEX, we’re proud to be recognized as a great place to work and a leader in the promotion and practice of diversity, equity and inclusion. If you’re excited about working for our company and believe you’re a good fit for this role, we encourage you to apply. You may be exactly the person we’re looking for!