Senior Data Engineer GCP (M/K)

Experis to światowy lider rekrutacji specjalistów i kadry zarządzającej w kluczowych obszarach IT. Z nami znajdziesz konkurencyjne oferty zatrudnienia oraz ciekawe projekty IT skierowane zarówno do ekspertów z wieloletnim doświadczeniem, jak i osób, które dopiero zaczynają swoją przygodę w branży IT.

• 5+ years of experience in Data Engineering including hands-on production experience with GCP
• Strong project experience with BigQuery data layer modeling, partitioning, clustering, and cost optimization
• Experience with dbt models, tests, and documentation
• Experience with Apache Airflow / Cloud Composer
• Proficient in Python and PySpark
• Proficient in SQL
• Experience with Terraform
• Experience building lakehouse / data warehouse solutions using medallion architecture
• Experience with CI/CD (preferably GitHub Actions), Git, and pipeline testing and monitoring
• Practical knowledge of data security on GCP including IAM, policy tags / column-level security, and row-level security
• Very good command of English

Nice to have:

• Experience with Dataplex / Data Catalog, data lineage, and metadata management
• Familiarity with Cloud DLP / Sensitive Data Protection
• Experience with Dataproc and Pub/Sub
• Experience in banking sector or regulated industries
• Experience working in platform-oriented model (Hub & Spoke, data mesh, data products)
• Google Professional Data Engineer certification

• Build and maintain data pipelines using dbt and orchestrate workflows with Apache Airflow / Cloud Composer
• Develop data processing components in Python and PySpark
• Design and develop the Gold and Platinum layers of the medallion architecture in BigQuery
• Optimize BigQuery performance and costs through partitioning, clustering, and FinOps practices
• Build and maintain CI/CD pipelines using GitHub Actions and manage infrastructure as code with Terraform
• Implement the data security model including IAM, RBAC/ABAC, policy tags, and DLP
• Contribute to Data Governance standards, including Dataplex, metadata management, and data lineage
• Conduct code reviews and help define team engineering standards and best practices
• Provide technical guidance to domain teams within the Hub & Spoke model and promote data engineering best practices on GCP