GCP Data Engineer

You will be:

• designing, building, and maintaining scalable data pipelines on GCP,

• developing and optimizing data models using BigQuery and dbt,

• building and managing real-time and batch data processing using Kafka,

• ensuring data quality, consistency, and reliability across pipelines,

• supporting migration of legacy data systems into modern cloud-based architecture,

• collaborating with Data Architects, Platform Engineers, and Analytics teams,

• enabling self-service data capabilities for internal consumers (data products mindset),

• implementing monitoring, logging, and observability for data pipelines,

• optimizing performance and cost of data workloads in GCP,

• contributing to best practices in data governance and data engineering standards.

Your profile:

• strong hands-on experience with BigQuery,

• solid experience with dbt (data transformations, modeling),

• experience working with Kafka (streaming data pipelines),

• strong skills in building data pipelines (batch and/or streaming),

• very good knowledge of SQL,

• experience with cloud data platforms (preferably GCP),

• understanding of data modeling concepts (DWH, ELT/ETL),

• experience working in complex, multi-team environments,

• strong problem-solving skills and ownership mindset,

• good communication and collaboration skills,

• experience with data platform or data mesh concepts,

• familiarity with CI/CD for data workflows,

• knowledge of Python or Scala for data processing,

• experience with data quality / validation frameworks,

• understanding of data governance and security best practices,

• experience in cloud migration projects,

• familiarity with orchestration tools (e.g. Airflow, Cloud Composer),

• 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 real-time analytics use cases,

• exposure to self-service data platforms / data products,

• knowledge of cost optimization in BigQuery,

• experience in large-scale enterprise transformations,

• GCP certifications (e.g. Professional Data Engineer),

• experience working in international distributed teams,

• 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.

   

Recruitment Process:

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