GCP Data Engineer

Quick Facts

• Role: Data Engineer (GCP)

• Focus: Scalable data pipelines on Google Cloud Platform

• Data Warehouse: BigQuery

Description

Build and maintain scalable data pipelines on Google Cloud Platform. You will work with BigQuery for data modeling, query and cost optimization, and reliable performance, while integrating and transforming data from multiple sources and orchestrating workflows with Apache Airflow / Cloud Composer.

Responsibilities

• Design, implement, and maintain scalable data pipelines on Google Cloud Platform

• Model data and optimize BigQuery queries for performance and cost; ensure reliability

• Integrate and process data from files, databases, APIs, and event streams

• Orchestrate data workflows using Apache Airflow / Cloud Composer

• Build and maintain CI/CD solutions for data pipelines and supporting infrastructure

• Manage cloud infrastructure using Infrastructure as Code with Terraform

• Ensure data quality, pipeline monitoring, and fast incident response

• Collaborate with analytics, BI, and product teams to deliver stable, well-documented data

• Contribute to data architecture development and define data engineering best practices

Requirements

• Min. 4 years of experience as a Data Engineer (or similar) in production data environments

• Very good knowledge of GCP, especially BigQuery (modeling, query optimization) and Cloud Storage

• Experience designing, building, and maintaining data pipelines (batch and/or streaming)

• Very good SQL and Python knowledge for data processing and orchestration

• Experience with workflow orchestration (Apache Airflow / Cloud Composer)

• CI/CD implementation experience for data solutions (GitHub Actions, GitLab CI, Cloud Build)

• Infrastructure as Code knowledge, with Terraform

• Experience with large data volumes, including performance and reliability

• Fluent communication in English

• Must be located in Poland and fluent in Polish

Benefits

• Opportunity to work with experts and develop toward Data Engineering, Big Data, or Machine Learning

• Real impact on data projects