GCP Analytics Engineer New Poland

Xebia Group; Polska; Hybrid; PLN 180,000 - 260,000; Full time

Job summary

Xebia Group in Poland is seeking a data engineer to design, build, and maintain dbt-based transformation frameworks and analytical data models on modern data platforms. You will collaborate with Data Engineering, DevOps, and Platform teams, optimize dbt performance, manage versioning, and document governance and quality procedures to ensure scalable analytics.

Join a global AI-first engineering partner delivering data-driven solutions across industries, leveraging AWS, Azure, GCP, Databricks,

Qualifications

• Strong commercial experience with dbt.
• Hands-on experience with BigQuery.
• Experience designing and building analytical or transformation layers on modern data platforms.
• Experience developing and maintaining data models for enterprise analytics environments.
• Understanding of data model lifecycle management and versioning.
• Experience with Docker-based deployment approaches.
• Familiarity with Python.
• Experience optimizing the performance and operational efficiency of data transformations.
• Strong communication and documentation skills.

Responsibilities

• Design, develop, and maintain dbt-based transformation frameworks.
• Build and optimize data models supporting Silver and Gold data layers.
• Optimize dbt execution performance and operational efficiency.
• Support versioning and lifecycle management of dbt artifacts.
• Separate dbt models from runtime Docker images and implement controlled distribution mechanisms.
• Evaluate and implement alternative execution approaches using native BigQuery capabilities where appropriate.
• Consolidate and simplify data transformation workflows.
• Collaborate with Data Engineering, DevOps, and Platform teams.
• Support data quality and transformation governance initiatives.
• Prepare and maintain technical documentation.

Skills

dbt

BigQuery

Data modeling

Python

Docker

Documentation

Communication

Tools

Apache Airflow

Kubernetes

Google Cloud Storage

Job description

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 Millennium, ING, Play, Edenred, Arabian Drilling, FedEx, Leroy Merlin, Truecaller, Volotea, Schmitz Cargobull, 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:

design, develop, and maintain dbt-based transformation frameworks,

build and optimize data models supporting Silver and Gold data layers,

optimize dbt execution performance and operational efficiency,

support versioning and lifecycle management of dbt artifacts,

separate dbt models from runtime Docker images and implement controlled distribution mechanisms,

evaluate and implement alternative execution approaches using native BigQuery capabilities where appropriate,

consolidate and simplify data transformation workflows,

collaborate with Data Engineering, DevOps, and Platform teams,

support data quality and transformation governance initiatives,

prepare and maintain technical documentation.

Your profile:

strong commercial experience with dbt,

hands-on experience with BigQuery,

experience designing and building analytical or transformation layers on modern data platforms,

experience developing and maintaining data models for enterprise analytics environments,

understanding of data model lifecycle management and versioning,

experience with Docker-based deployment approaches,

familiarity with Python,

experience optimizing the performance and operational efficiency of data transformations,

strong communication and documentation skills.

Nice to have:

experience with Apache Airflow,

experience with BigQueryInsertJobOperator or similar orchestration approaches,

familiarity with Google Cloud Storage and Kubernetes,

experience optimizing cloud processing costs,

experience in regulated industries, including banking or financial services,

experience supporting data quality and governance initiatives.

Recruitment Process:

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