Data Engineer RibbitZ

Our client RibbitZ is looking for Data Engineer (Microsoft Fabric Azure Databricks) in Dubai.
Role Summary

We are seeking a Data Engineer with hands-on experience in Azure-based data platforms and Microsoft Fabric to build scalable data pipelines and analytics solutions.
The ideal candidate will have strong skills in PySpark SQL and modern data engineering frameworks with exposure to lakehouse architecture real-time data processing and cloud-native tools.
Key Responsibilities
1. Data Pipeline Development

• Develop and maintain ETL/ELT pipelines using Azure-native tools and frameworks.
  
• Process structured and semi-structured data (JSON XML CSV APIs).
  
• Implement incremental data loading and transformation logic.
  
• Ensure data quality validation and consistency across pipelines.
  

2. Microsoft Fabric & Lakehouse Implementation

• Work with Microsoft Fabric components including:
  
  • Eventstream
    
  • Eventhouse
    
  • Fabric Pipelines
    
• Implement Lakehouse architecture using Medallion model (Bronze Silver Gold).
  
• Utilize Delta Lake for efficient storage and processing.
  

3. Azure Data Platform Development

• Build data solutions using:
  
  • Azure Data Factory (ADF)
    
  • Azure Databricks
    
  • ADLS Gen2
    
• Ingest data from multiple sources:
  
  • ERP / SAP systems
    
  • APIs and external data sources
    
• Support cloud-based data integration and transformation.
  

4. Big Data Processing

• Develop data transformation workflows using:
  
  • PySpark / Apache Spark
    
• Optimize pipelines using:
  
  • Partitioning caching and efficient joins
    
• Work on both batch and streaming data processing.
  

5. Data Modeling & Analytics

• Build analytics-ready datasets for reporting and BI.
  
• Apply dimensional modeling concepts.
  
• Deliver curated datasets for downstream consumption.
  

6. Real-Time Data Processing (Preferred)

• Implement real-time data pipelines using:
  
  • Microsoft Fabric Eventstream
    
  • IoT / streaming data sources
    
• Enable real-time dashboards and monitoring use cases.
  

7. Analytics & Visualization Support

• Integrate data pipelines with Power BI dashboards.
  
• Support business teams with clean and reliable datasets.
  

8. Modern Data Tools & Frameworks

• Work with:
  
  • dbt for transformation and modeling
    
  • Snowflake for analytics workloads
    
• Develop modular reusable and scalable data workflows.
  

9. DevOps & Best Practices

• Use GitHub / Git for version control.
  
• Follow CI/CD and deployment best practices.
  
• Document data pipelines and processes.
  

Required Skills & Technologies
Core Skills

• Python / PySpark
  
• SQL (Strong proficiency)
  
• ETL/ELT pipeline development
  

Cloud & Tools

• Microsoft Azure:
  
  • Azure Data Factory (ADF)
    
  • Azure Databricks
    
  • ADLS Gen2
    
• Microsoft Fabric (preferred)
  

Data Engineering Concepts

• Lakehouse architecture
  
• Delta Lake
  
• Data modeling (basic dimensional modeling)
  
• Incremental data processing
  

Additional Tools

• dbt (preferred)
  
• Snowflake (good to have)
  
• Power BI
  

Experience Requirements

• 35 years of experience in Data Engineering
  
• Hands-on experience in:
  
  • Azure data ecosystem
    
  • Databricks / PySpark
    
  • Building data pipelines and transformations
    

Educational Qualifications

• Bachelors degree in Computer Science / Engineering / IT
  
• Relevant certifications are a plus:
  
  • Microsoft Fabric (DP-600 / DP-700)
    
  • Azure Data Engineer (DP-203)
    
  • Databricks certifications
    

Soft Skills

• Strong analytical and problem-solving skills
  
• Ability to work in a collaborative Agile environment
  
• Good communication skills
  
• Attention to detail and data accuracy
  

Nice to Have

• Exposure to real-time/streaming data pipelines
  
• Experience with API integrations
  
• Basic understanding of machine learning workflows
  
• Experience working with ERP/SAP data