DE&A - Core - Advanced Visualization & Cloud Reporting - Azure Analysis Services

Role Overview

We are seeking a skilled Data Integration & Middleware Engineer to implement and manage scalable data pipelines and middleware solutions. The role will focus on orchestrating data workflows using Azure technologies such as Azure Data Factory (ADF), Azure Blob Storage, and Azure SQL Database, ensuring efficient ETL/ELT processing and high-quality data delivery.

Key Responsibilities

• Manage end-to-end data integration pipelines using Azure Data Factory (ADF)


• Orchestrate and monitor data workflows, ensuring reliability, performance, and error handling


• Implement\ Manage ETL/ELT processes for data ingestion, transformation, and loading


• Manage and optimize data storage solutions using Azure Blob Storage


• Maintain structured data models in Azure SQL Database / Azure DB


• Ensure data quality, validation, and governance across pipelines


• Support integration with on-premise and cloud-based systems


• Perform performance tuning and cost optimization across the data platform

 Technical Skills Required

Core Skills – Must Have

• Strong experience with Azure Data Factory (ADF) for orchestration


• Hands-on experience with ETL/ELT development


• Experience with Azure Blob Storage / Data Lake


• Proficiency in Azure SQL Database / SQL Server


• Understanding of data warehousing concepts and data modeling


• Knowledge of DevOps, CI/CD pipelines for data workflows

Nice to Have

• Experience with Azure Databricks or Synapse Analytics


• Knowledge of data pipeline optimization and monitoring


• Familiarity with API integrations and data connectors


• Exposure to data governance and security practices


• Azure certifications (e.g., AZ-900, DP-203)


• Experience with real-time data processing frameworks (Event Hub, Service Bus)

 Soft Skills

• Strong analytical and problem-solving abilities


• Clear communication and stakeholder management skills


• Ability to work in a collaborative, cross-functional environment


• Attention to detail and commitment to data quality