Azure Databricks Data Engineer - Innovative Cloud Projects

Further Details

Seeking a skilled Azure Databricks Data Engineer with 4-5 years of experience to join Bluetab, an IBM Company. This position involves developing and optimizing data pipelines using Scala, Python, or PySpark on Spark and Databricks within cloud environments. The role is ideal for professionals passionate about Big Data and complex challenges. Key responsibilities include designing Data Lake and Data Warehouse architectures on Azure, transforming data at scale, optimizing queries in Databricks, and integrating multiple data sources. Collaboration with multidisciplinary teams is essential for continuous improvement in data ingestion and processing.

Azure Databricks Data Engineer in Spain

Bluetab, an IBM Company, recognized as a Great Place to Work, is seeking passionate Azure Databricks Data Engineers to join their innovative team. This is an excellent opportunity to work on national and international projects, optimizing data strategies on cloud platforms.

The company is looking for professionals with at least 4-5 years of experience in Scala, Python, or PySpark, focusing on Spark and Databricks within cloud environments. If you are driven by Big Data challenges and enjoy optimizing large-scale data pipelines, this role offers competitive compensation and significant career growth.

• Job Title: Azure Databricks Data Engineer
• Company: Bluetab, an IBM Company
• Location: Aragón, Spain
• Required Experience: 4-5 years
• Key Skills: Scala, Python, PySpark, Spark, Databricks, SQL, Cloud (Azure), Terraform, Airflow
• Benefits: Competitive salary, flexible teleworking, flexible hours, 23 days vacation, restaurant card, medical insurance, flexible benefits plan, continuous training, career development program.

Skills

• Solid experience in development with Scala, Python, or PySpark on Spark for distributed processing
• Experience with Databricks and knowledge of Data Lakehouse architectures
• Advanced SQL knowledge, query optimization, and scalable data modeling
• Experience in deployments and automation with tools like Terraform, Airflow, or similar
• Familiarity with cloud environments (Azure, AWS, or GCP)
• Analytical mindset focused on efficiency, optimization, and scalability of data processes
• Collaborative attitude and passion for innovation, working in teams to solve complex challenges

Duties and Responsibilities:

• Develop and optimize data pipelines in Scala, Python, or PySpark, ensuring performance, quality, and scalability
• Design and build Data Lake and Data Warehouse architectures in cloud environments (primarily Azure, but also AWS or GCP)
• Transform large-scale data using Spark, applying best practices for distributed processing
• Optimize queries and storage in Databricks, ensuring efficient data consumption and cost reduction
• Integrate multiple data sources, ensuring their quality, consistency, and traceability
• Collaborate with multidisciplinary teams, driving continuous improvement in data ingestion, transformation, and exploitation processes

How to apply

• 👉 Prepare Your Application: Ensure your CV highlights your experience in Scala, Python, PySpark, Spark, Databricks, advanced SQL, cloud environments (Azure), and automation tools like Terraform or Airflow.
• 💼 Submit Your Application: Click on the 'Apply Now' link to proceed to the official application portal.
• 📝 Complete the Form: Fill out the application form accurately with your personal and professional details.
• 📅 Deadline: Please ensure your application is submitted before the closing date of December 18, 2026.
• 🌐 Learn More: Visit the company's career page for more details on their culture and projects.
• 🚀 Start Your Journey: If you are ready to advance your career in data engineering with a leading tech company, this is your opportunity!