Senior Analytics Engineer (AWS)

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:

• building and maintaining the canonical business model on Iceberg: governed entities and the relationships needed for project performance reporting, stable across changes in the underlying source storage,
• developing curated data marts,
• modeling the assembly and sub-assembly hierarchy from the Neptune graph, required for BOM and project reporting,
• structuring dbt projects across staging, intermediate, and marts layers using ref(), macros, and packages to eliminate duplication,
• implementing the data quality framework: schema and freshness tests, dbt-expectations assertions, and dbt-elementary observability feeding a single quality gate,
• handling schema evolution to prevent reporting disruptions: versioning tables, applying data contracts, and managing structural changes on a case-by-case basis,
• contributing dbt models to the CI/CD pipeline (slim builds, linting, PR reviews) and supporting scheduled orchestration through Airflow and Cosmo,
• collaborating with Data Analysts on mart design and with Data Engineers on upstream data structures; supporting client knowledge transfer.

Your profile:

• advanced SQL and strong data modeling skills (dimensional, canonical, medallion-style layering),
• experience with dbt (dbt-core), including tests, macros, sources, and documentation,
• experience with Apache Iceberg and Athena in an AWS lakehouse environment,
• familiarity with analytics engineering practices: version control, code review, and modular design,
• previous exposure to dbt adapters for AWS (dbt-athena, dbt-glue), dbt-expectations, and dbt-elementary; experience with Airflow orchestration, ideally Astronomer Cosmos,
• understanding of partitioning and pre-aggregation techniques for SLA-driven performance,
• Python skills for supporting transformations and tooling.

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

Nice to have:

• previous exposure to graph data (Neptune) and CDC-driven data,
• Snowflake and Sigma experience, given Xebia's partnership and likely future work.

Recruitment Process:

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