We are looking for an experienced Data Engineer to join our growing data team. The idóneo candidate will have a strong background in building and maintaining scalable data pipelines, managing infrastructure as code, and ensuring smooth CI/CD integration across environments. You’ll work closely with cross‑functional teams to design, implement, and optimize data solutions that drive key business insights.

Key Responsibilities

- Design, develop, and maintain data pipelines and workflows in Databricks .
- Build and manage data transformation models using dbt (Data Build Tool) .
- Implement and support infrastructure automation with Terraform and Kubernetes .
- Develop and maintain CI/CD pipelines for data integration and deployment processes.
- Collaborate with data scientists, analysts, and engineers to ensure efficient data flow and architecture.
- Monitor, optimize, and troubleshoot data infrastructure for performance and scalability.
- Work with Azure DevOps to manage repositories, pipelines, and deployments.
- Ensure best practices in data quality, version control,



and infrastructure reliability.

Required Skills & Qualifications

- 4+ years of hands‑on experience as a Data Engineer or in a similar role.
- Strong proficiency in Databricks and dbt .
- Experience with Azure DevOps for pipeline orchestration and version control.
- Solid understanding of Kubernetes for container orchestration.
- Experience implementing infrastructure as code using Terraform .
- Proven experience setting up and managing CI/CD pipelines for data solutions.
- Strong understanding of data modeling , ETL processes , and cloud‑based data architectures .
- Excellent problem‑solving skills and attention to detail.
- Strong communication and collaboration abilities within agile teams.

Seniority level

- Mid‑Senior level

Employment type

- Contract

Job function

- Information Technology

Industries

- Staffing and Recruiting

Location: Madrid, Community of Madrid, Spain

#J-18808-Ljbffr

📌 Data Engineer (Madrid/Barcelona)
🏢 Senovo IT
📍 Madrid