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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:

designing, building and maintaining data models (mainly in dbt/Dataform) on top of BigQuery,
developing and optimizing analytical datasets and data marts for business consumption,
collaborating with data engineers and business stakeholders to translate requirements into scalable data solutions,
implementing data transformation logic and ensure data quality, testing, and validation,
supporting migration of existing pipelines from AWS / Snowflake / Azure into GCP,
working with ingestion pipelines (Pub/Sub, Datastream, Dataflow) and ensure alignment with downstream reporting needs,
contributing to governance, data cataloging, and lineage (Knowledge Catalog),
enabling self-service analytics through reusable models, templates, and standards,
validating data consistency during migration and support cutover (parity vs legacy systems),
supporting BI layer (e.g. QuickSight) and ensure consistency of KPIs across domains,
participating in establishing best practices for analytics engineering and data product development.

Your profile:

strong experience as Analytics Engineer / Data Engineer with focus on analytics layer,
hands-on experience with dbt (or Dataform) and SQL-based transformations,
experience with GCP stack (BigQuery, Cloud Storage, Composer/Airflow),
strong SQL skills and experience building data models (dimensional modeling, data marts),
experience working with modern data platforms / lakehouse architectures,
understanding of data pipelines, ETL/ELT processes, and orchestration (Airflow/Dagster or similar),
experience with data validation, testing, and data quality frameworks,
ability to work with stakeholders and translate business needs into data models,
familiarity with data migration projects (replatforming, consolidation),
experience with CI/CD for data (e.g., Terraform, GitHub Actions, Cloud Build),
knowledge of data governance, cataloging and lineage tools,
exposure to streaming or near real-time data processing,
familiarity with AI/ML or analytics enablement use cases,
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.

Nice to have:

experience with Knowledge Catalog / data catalog tools Experience with BI tools (e.g., QuickSight or similar),
exposure to self-service data platforms,
understanding of FinOps / cost optimization in cloud data platforms,
experience in highly distributed enterprise environments.

Recruitment Process:

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

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Senior Analytics Engineer (GCP)

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