Senior Data Engineer Cloud And Analytics - RibbitZ

Our client RibbtZ is looking for Senior Data Engineer (Cloud Analytics) to work remotely.

Role Summary

We are seeking a highly skilled Senior Data Engineer with strong expertise in cloud-based data platforms, big data processing, and modern data architectures. The ideal candidate will have hands-on experience in building scalable data pipelines, implementing lakehouse architectures, and enabling advanced analytics and machine learning use cases across enterprise environments.

Key Responsibilities

Data Engineering & Architecture

• Design and implement scalable data pipelines (ETL/ELT) for batch and real-time processing.
• Build and maintain modern data platforms using lakehouse architecture (Bronze, Silver, Gold layers).
• Develop and optimize data models (star/snowflake schemas) for analytics and reporting.
• Ensure high data quality, integrity, and governance across systems.
  
  
  

• Develop and deploy solutions on Microsoft Azure and/or AWS ecosystems.
• Work with services such as:
• Azure Data Factory, Azure Databricks, ADLS Gen2
• Azure SQL, Key Vault, Azure DevOps
• AWS S3, Redshift, EMR, Glue, Lambda
  
• Implement secure, scalable, and cost-efficient data storage solutions.
  
  

• Develop large-scale data processing workflows using:
• Apache Spark / PySpark
• Kafka, Hive, Hadoop, Airflow
  
• Optimize performance of distributed data processing systems.
  
  

• Implement Microsoft Fabric-based data solutions including:
• Lakehouse architecture
• Medallion design (Bronze/Silver/Gold)
• Delta Lake optimization
  
• Build Fabric pipelines and integrate with Power BI.
  
  

• Lead data migration initiatives from legacy/on-prem systems to cloud platforms.
• Integrate multiple data sources (SAP, Oracle, SQL Server, APIs, etc.).
• Implement incremental data loading and performance optimization techniques.
  
  
  

• Enable business intelligence and reporting using tools like:
• Power BI, SSRS, Kibana, Grafana
  
• Implement Row-Level Security (RLS) and data access controls.
  
  

• Support ML pipelines using frameworks such as:
• Scikit-learn, TensorFlow, PyTorch, Keras
  
• Collaborate with data scientists for model deployment and integration.
  
  

• Implement CI/CD pipelines using Azure DevOps/Git.
• Use Docker for containerization.
• Automate data validation, monitoring, and deployment processes.
  
  
  

• Implement monitoring using Azure Monitor, Log Analytics, etc.
• Ensure compliance with data governance frameworks (e.g., Purview).
• Maintain security standards using Key Vault, IAM, and encryption mechanisms.
  
  
  

• Strong programming skills in Python and/or Java
• Advanced SQL and data warehousing concepts
• Hands-on experience with:
• Spark / PySpark
• ETL/ELT pipeline development
• Data modeling and optimization
  
  
  

• Experience with Microsoft Azure (preferred) or AWS
• Exposure to Databricks, ADF, ADLS, Snowflake is highly desirable
  
  
  

• Apache Spark, Kafka, Hive, Airflow
  
  
  

• Git, Docker, CI/CD pipelines
• BI tools (Power BI preferred)
  
  
  

• 7–10 years of experience in Data Engineering / Big Data
• Proven experience in:
• Designing scalable data architectures
• Cloud data platform implementations
• Data migration and transformation projects
  
  
  

• Bachelors degree in Computer Science, Engineering, or related field
• Certifications in Azure/AWS/Data Engineering are a plus
  
  
  

• Strong problem-solving and analytical thinking
• Ability to work in Agile/DevOps environments
• Excellent stakeholder communication and collaboration skills
• Ability to lead technical discussions and mentor junior engineers
  
  
  

• Experience with Microsoft Fabric
• Exposure to real-time streaming architectures
• Knowledge of AI/ML pipelines