Data Engineer GCP

DS STREAM REMOTE WARSAW KATOWICE KRAKÓW WROCŁAW POZNAŃ 2026-09-30

Must Have



  • Over 3 years of experience in Data Engineering and building production-scale data platforms.

  • Strong programming skills in Python and SQL.

  • Advanced experience with data modeling, ETL development, and multiple data formats.

  • Strong knowledge of Google Cloud Platform and cloud-native architecture design.

  • Expert knowledge of Apache Airflow for workflow orchestration and automation.

  • Hands-on experience with Apache Spark for batch and high-volume streaming workloads.

  • Good understanding of CI/CD and DevOps tools such as GitHub Actions or Kubernetes.


Nice to Have



  • Experience with MLOps and ML deployment in production, preferably with Vertex AI.

  • Practical experience with Terraform for Infrastructure as Code.

  • Experience building scalable REST APIs for data or ML services.

  • Strong testing practices, including TDD and unit/integration tests for Spark and Airflow.

  • Knowledge of Scala for high-performance data processing.

Data Engineer


We’re looking for an experienced Data Engineer to build, scale, optimize, and maintain reliable data platforms. You’ll work on real-time pipelines, ML infrastructure, attribution data processing, and cloud-native solutions in a high-volume production environment.


Tech Stack



  • GCP

  • Apache Spark, dbt, BigQuery

  • Python, SQL, Scala

  • Apache Airflow

  • Terraform, GitHub Actions, Docker, Kubernetes

  • VertexAI

,[Build and maintain large-scale advertising data pipelines for clicks, impressions, attribution, and event processing. , Improve attribution modeling logic to support better optimization and business decisions. , Ensure high availability, performance, stability, and scalability of real-time data workflows. , Design and support production-grade ML model serving infrastructure., Develop and manage dbt datasets for model training, experimentation, and Feature Store integration. ] Requirements: Google Cloud Platform, ETL, Airflow, Python, SQL, Spark, DevOps, CI/CD, Kubernetes, MLOps, AI, Scala, REST API, Terraform, VertexAI Additionally: Sport subscription, Training budget, Private healthcare, Flat structure, Small teams, International projects.
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