Data Platform Architect (Snowflake)

Who We Are

While Xebia is a global tech company, our journey in CEE started with two Polish companies – PGS Software, known for world-class cloud and software solutions, and GetInData, a pioneer in Big Data. Today, we’re a team of 1,000+ experts delivering top-notch work across cloud, data, and software. And we’re just getting started.

What We Do

We work on projects that matter – and that make a difference. From fintech and e-commerce to aviation, logistics, media, and fashion, we help our clients build scalable platforms, data and AI solutions, and cutting-edge applications to shape the future of tech. Our clients include McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more.

We value smart tech, real ownership, and continuous growth. We use modern, open-source stacks, and we’re proud to be trusted partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS. Fun fact: we were the first AWS Premier Partner in Poland!

Beyond Projects

What makes Xebia special? Our community. We support tech communities, organize meetups (Software Talks, Data Tech Talks), and have a culture that actively support your growth via Guilds, Labs, and personal development budgets — for both tech and soft skills. It’s not just a job. It’s a place to grow.

What sets us apart? 

Our mindset. Our vibe. Our people. And while that’s hard to capture in text – come visit us and see for yourself.

• responsible for end-to-end ownership of the Snowflake-based data platform architecture, from design through production,
• ensuring architectural consistency and quality across all implementation teams,
• driving execution across distributed teams, including close collaboration with India-based delivery teams as well as acting as the primary technical counterpart for senior US-based stakeholders - operating in global delivery models across multiple time zones,
• translating business objectives into concrete, executable technical plans,
• making fast, pragmatic architectural decisions while effectively managing trade-offs,
• unblocking teams and resolving cross-team technical dependencies,
• defining and enforcing architectural standards, patterns, and guardrails,
• ensuring production readiness, including scalability, security, governance, and operational robustness,
• supporting rollout and early production phases when required.

• Technical skills:
  • deep, hands‑on experience with Snowflake as a core enterprise data platform,
  • proven track record of delivering large‑scale data platforms, not just designing them,
  • strong understanding of modern enterprise data platform architectures,
  • practical experience with data ingestion, transformation, and modeling patterns,
  • hands‑on experience with dbt or equivalent transformation frameworks,
  • solid understanding of cloud platforms (even if Snowflake is the core layer),
  • strong knowledge of security, governance, and operational considerations in production systems.
• Leadership & Delivery:
  • ability to take full technical ownership without supervision,
  • confidence working directly with senior client leadership and decision makers,
  • strong decision‑making skills under ambiguity and time pressure,
  • delivery‑oriented mindset with high accountability,
  • ability to lead by authority, clarity, and execution discipline (without formal authority),
  • excellent communication skills,

• Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery.

Work from the European Union region and a work permit are required.

• experience supporting early production or hypercare phases,
• background in highly regulated or data‑sensitive environments,
• previous experience acting in a Field CTO, Principal Architect, or equivalent role,
• experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work,
• interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches.

CV review – HR call – Interview – Client Interview – Decision