Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.
We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.
In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.
You will be:
- owning the development and maintenance of the AI layer supporting business analytics, including Talk2Data and agent-ready data,
- defining, implementing and testing the analytical components of the Talk2Data solution – from specification and business validation through to release,
- building and continuously improving the evaluation framework for AI response quality, including defining metrics, collecting representative Q&A pairs, establishing ground truth and monitoring quality scores over time,
- translating business needs, use cases and business rules into clear requirements, acceptance criteria and analytical specifications,
- collaborating with Data Engineers to define dimensional data models using a star schema approach, propose data quality checks, review merge requests and support deployments,
- working with large datasets and cloud-based data platforms to validate data quality, structure and suitability for AI-powered analytics,
- collaborating with Product Leads, Business Owners and other stakeholders to confirm data ownership and ensure alignment with data governance standards,
- preparing presentations, guidelines and supporting materials explaining the established approach to both technical and non-technical audiences,
- facilitating enablement initiatives such as AI Office Hours for data teams and business users, as well as dedicated sessions with Product Leads,
- continuously improving the quality and performance of solution by analysing user feedback, product analytics and evaluation results,
- driving the adoption of AI-assisted analytics solutions across the organization,
- leading and validating Proofs of Concept related to AI solution implementation and new business use cases,
- diagnosing and escalating technical issues related to AI tooling and integrations, including Claude, Power BI MCP and connectors,
- evaluating and comparing alternative AI solutions, tools and implementation approaches,
- ensuring that AI-generated outputs and analytical solutions are critically validated before being introduced into business processes.
Your profile:
- at least 5 years of experience in an analytical role,
- a strong background in business analytics, data engineering or a related discipline, with the ability to bridge technical details and business objectives,
- advanced proficiency in SQL and experience working with large datasets in cloud data platforms,
- a comprehensive understanding of data warehousing concepts, including dimensional data modelling and ETL/ELT processes,
- hands-on experience with LLM-based AI tools, such as Claude or similar solutions,
- practical understanding of how AI assistants are built and evaluated, including quality metrics, representative Q&A datasets, ground truth and ongoing performance monitoring,
- experience translating business needs into clear, well-documented requirements, analytical specifications and acceptance criteria,
- the ability to tailor communication, presentations and documentation to both technical and non-technical audiences,
- basic familiarity with Git, code review and version control processes, sufficient to read and review changes and coordinate the merging of work prepared by Data Engineers,
- knowledge of data governance and data cataloguing practices, including tools such as Atlan or similar platforms,
- strong stakeholder management and collaboration skills, with the ability to work effectively with Data Engineers, Product Leads, Business Owners and other cross-functional stakeholders,
- an analytical and critical mindset, with the ability to assess the quality, reliability and business relevance of AI-generated outputs,
- fluent in Polish and English,
- experience with Databricks would be an asset.
Work from the European Union region and a work permit are required.
Recruitment Process:
CV review – HR call – Interview – Client Interview – Decision