Senior Data & ai Engineer H/F
Role details
Job location
Tech stack
Job description
Nhood is a leader in real estate services, helping shape how data supports decision-making, transformation, and innovation across the business. Operating in the commercial real estate sector, the company is investing in modern data foundations that enable stronger analytics, better operational visibility, and new AI-driven opportunities.
This is an opportunity to join a broader international transformation journey and contribute to the evolution of a data ecosystem designed for scale, quality, and long-term value. You will work in an environment where data engineering and AI enablement come together to support impactful business initiatives.
As a Senior Data & AI Engineer, you will play a key role in building and advancing the data capabilities that underpin analytics and AI use cases. The role is centered on designing robust data solutions, improving the performance and reliability of core data platforms, and bringing technical expertise to projects that support business transformation in an international context.
Responsibilities
- Design and evolve data processing on an Azure Lakehouse architecture.
- Collect, integrate, structure, and model data.
- Optimize processing performance and ensure data quality.
- Prepare datasets for analytics and AI use cases.
- Promote AI-assisted development practices including code generation, refactoring, testing, and documentation.
- Provide technical expertise to support data projects in an international transformation context.
Requirements
At least five years of experience in Data Engineering, BI, or Cloud Data Engineering.Significant experience with Cloud and Lakehouse architectures.Strong command of Databricks, including Delta Lake and Lakehouse performance optimization.Expertise in data modeling, including analytical schemas, slowly changing dimensions (SCD), and data structuring.Familiarity with AI-assisted development tools., * At least five years of experience in Data Engineering, BI, or Cloud Data Engineering.
- Significant experience with Cloud and Lakehouse architectures.
- Strong command of Databricks, including Delta Lake and Lakehouse performance optimization.
- Expertise in data modeling, including analytical schemas, slowly changing dimensions (SCD), and data structuring.
- Familiarity with AI-assisted development tools.