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Data Engineer (Azure & Databricks)

External
Talan logoTalan · Málaga, Spain
Full-timeOn-site5d ago
AgileAzureCI/CDData ModelingdbtETL
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Responsibilities

  • Design and develop data pipelines using Azure and Databricks
  • Transform and model data using best practices (Star Schema, Data Vault)
  • Build and maintain ETL/ELT pipelines with DBT
  • Collaborate with data architects and analysts to define data structures
  • Ensure quality, performance, and scalability of data solutions
  • Version control and collaborate via GitLab
  • Work in an agile environment with distributed teams
  • Required:
  • 4-5 years of experience as Data Engineer or similar role
  • Hands-on experience with Databricks and Azure (Data Services)
  • Experience using DBT for transformations (at least some exposure)
  • Strong experience in data modeling (Star Schema; knowledge of Data Vault is a plus)
  • Experience working with VSCode and GitLab
  • Solid SQL skills and understanding of data pipelines

Requirements

  • Experience working in international or enterprise-scale environments
  • Exposure to Data Vault modeling in production
  • Knowledge of CI/CD for data pipelines
  • Experience in banking, financial services, or industrial sectors
  • What do we offer you?
  • Hybrid position based in Málaga, Spain
  • Possibility to manage work permits
  • Permanent, full-time contract.
  • Perks and Benfits such as private medical insurance , life insurance, language lesson, flexible remuneration,Smart Office Pack so that you can work comfortably from home
  • Training and career development.
  • Possibility to be part of a multicultural team and work on international projects.

Benefits

Flexible schedule

Additional Information

You will join a global data platform initiative focused on modernizing data architecture using cloud-native technologies. The project involves building scalable data pipelines and transforming legacy data models into modern analytics structures (Star Schema / Data Vault), leveraging Azure and Databricks. You'll collaborate with international teams and contribute to a robust, production-grade data ecosystem.


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