Data Engineer (GCP, Snowflake, dbt)

Role overview Build and improve data engineering and analytics solutions for a range of business needs, from warehouse modernization and CRM integration to commercial reporting and self-service analytics. The work combines pipeline development, data modeling, and collaboration with analysts, engineers, and business stakeholders to make data reliable and useful for decision-making.

Responsibilities - Design, develop, and optimize cloud data pipelines and models. - Create and maintain dbt models and complex transformations in Python and SQL. - Support warehouse modernization, BI platform migrations, and integrations across data sources. - Produce analytical datasets and reporting solutions for business decisions. - Improve data quality through testing, monitoring, and documentation. - Work with technical and business partners to deliver scalable data solutions.

Requirements - At least three years of commercial data engineering or analytics engineering experience. - Practical experience with GCP, especially BigQuery, and Snowflake. - Advanced Python and SQL skills, including complex transformations and query optimization. - Hands-on dbt experience developing, testing, and optimizing models. - Knowledge of data warehousing, modeling, ETL/ELT, and data architecture. - Experience with BI tools, workflow orchestration, Git, CI/CD, code reviews, automated testing, and data quality practices. - Strong problem-solving and communication skills, including English at C1 level or higher.

Nice to have - Familiarity with CRM platforms such as HubSpot or Salesforce, semantic layers, BI migrations, or warehouse refactoring.

Benefits and work setup - The role involves international data projects. The source also describes access to training and conferences, medical and wellbeing support, work equipment, team events, and a dedicated onboarding buddy.