Data Technical Lead
Pubblicato il 21-09-2026 - Ntt Data Europe & Latam in Emilia-Romagna
Who We Are
We are looking for an experienced Data Tehnical Lead. While the role will be supported by Solution Architects and Project Managers on the client side, the ideal candidate will demonstrate exceptional technical design capability, strong analytical and problem-solving skills, and the ability to lead teams through complex technical challenges while maintaining delivery momentum
Who We Are
We are looking for an experienced Data Tehnical Lead. While the role will be supported by Solution Architects and Project Managers on the client side, the ideal candidate will demonstrate exceptional technical design capability, strong analytical and problem-solving skills, and the ability to lead teams through complex technical challenges while maintaining delivery momentum
What You'll Be Doing
- Lead a team of approx. 5 developers to implement an Azure Data bricks and Azure Data Factory based solution
- Develop the technical solution spec, estimation, working closely with the Solution Architect
- Complete documentation required for the project relevant to the development team
- Create and monitor tasks for the development team and track through to completion
What You'll Bring Along
- BSc/MSc in Computer Science, Data Engineering, or related field
- Snowflake certifications highly desirable
- Experience: 8-10+ years in data systems, with 4+ years explicitly in leading teams
- Strong experience in Azure Databricks Workspace configuration and administration
- Expertise in Databricks cluster management, performance tuning, and troubleshooting
- Knowledge of Azure cost estimation and optimization
- Hands-on experience with Databricks AI capabilities, including Genie and Mosaic AI, and their integration into data solutions
- Proficiency in Databricks access and security management
- Ability to create and maintain Databricks Notebooks using SQL, Python, and R/Scala
- Solid understanding of DataFrames, data manipulation, and transformation techniques within Databricks
- Experien