Senior Software Engineer - Azure Databricks Migration

Profile: Software Engineer with expertise in Python development.

Knowledge required: Python, Shiny Python, Azure, Databricks, Data Factory, SQL, R.

Studies required: Technical Engineer.

Languages required: English, Spanish is a plus.

Minimum experience required: 5 to 7 years of technical experience.

Location: remote in EU.

Rate: 290€-300€/day.

Description

Lead the migration of applications from Posit (R/RShiny) to Databricks Apps using Python and Shiny for Python within the Azure ecosystem, supporting the transition to Databricks as the primary data platform. The role involves analysing existing applications, defining migration strategies, leveraging AI tools for code transformation, and developing data pipelines with Azure Data Factory, Databricks, and Azure SQL.

You will collaborate with cross-functional teams, act as a technical point of contact, troubleshoot issues, and manage multiple priorities to ensure high-quality delivery and customer satisfaction.

The ideal candidate has a degree in IT or a related field, experience with Azure and Databricks, a strong background in application migration, and proficiency in Python, SQL, and R. Knowledge of cloud and serverless architectures, database design, and tools such as Azure DevOps is required, along with strong communication skills and English proficiency (B2+). Spanish is a plus.

Specific expertise

• Advanced Python development (including data processing and backend logic).
• Strong experience with Databricks (workflows, notebooks, and app deployment).
• Proficiency in Azure ecosystem: Azure Data Factory, Azure SQL Database, and Azure DevOps.

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• Experience migrating applications from R / RShiny to Python-based frameworks (e.g., Shiny for Python).
• Solid understanding of data engineering concepts (ETL/ELT pipelines, data modeling, performance optimization).
• Experience with cloud-native and serverless architectures in Azure.
• Proficiency in SQL for data querying, transformation, and optimization.
• Familiarity with R and RShiny for legacy system analysis and migration.
• Experience integrating and leveraging AI-assisted development tools for code transformation.
• Knowledge of CI/CD practices and version control systems (e.g., Git).
• Understanding of API integration and application architecture principles.