We are seeking an experienced Azure Data Engineer with deep expertise in Azure Data Factory (ADF), Azure SQL, and Power BI to design, develop, modernize, integrate, and support enterprise-scale data engineering and analytics solutions.

The role involves building scalable and reusable ETL/ELT pipelines, implementing robust data integration frameworks, optimizing data models and database performance, and delivering reliable reporting and analytics solutions across enterprise systems.

Location & Work Arrangement

- Location: Anywhere in India
- Work Model: Fully Remote

Notice Period : 30 days or less or Immediate Joiner

Key Responsibilities:

A. Azure Data Engineering & Integration

- Design, develop, deploy, and support enterprise data integration solutions using Azure Data Factory.
- Build scalable ETL/ELT pipelines for data ingestion, transformation, validation, and publishing across Azure Data Lake, Azure SQL, data warehouses, Dynamics 365 Finance & Operations, APIs, and external systems.
- Develop reusable, metadata-driven pipeline frameworks aligned with enterprise architecture and engineering standards.
- Implement incremental data loads, Change Data Capture (CDC), orchestration, scheduling, and dependency management.
- Integrate data from ERP systems, relational databases, APIs, and other enterprise applications.

B. Azure Data Factory Development

- Develop and maintain ADF pipelines, mapping data flows, triggers, linked services, datasets, and integration runtimes.
- Implement parameterization, dynamic pipeline execution, reusable components, and configuration-driven processing.
- Configure data validation, reconciliation, exception handling, logging, monitoring, and failure-recovery mechanisms.
- Optimize pipeline performance, reliability, scalability, and resource utilization.
- Support production deployments, troubleshooting, and ongoing enhancements.

C. Azure SQL & Database Optimization

- Design, develop, and optimize Azure SQL databases, tables, views, stored procedures, and data models.




- Develop efficient T-SQL queries and implement indexing strategies to improve database performance.
- Perform query tuning, execution-plan analysis, and performance troubleshooting.
- Design and maintain data structures that support high-volume data processing, reporting, and analytics.
- Implement data quality checks, reconciliation logic, and efficient data-processing patterns.

D. Power BI & Analytics

- Develop and maintain Power BI datasets, semantic models, dashboards, scorecards, and reports.
- Design star schemas, dimensional models, and reporting data marts optimized for analytical workloads.
- Build effective relationships, measures, and calculations to support business reporting requirements.
- Optimize semantic models and report performance for scalability and usability.
- Collaborate with business stakeholders to translate reporting requirements into reliable analytical solutions.

E. Data Quality, Monitoring & Production Support

- Implement data validation, reconciliation, exception handling, and data quality controls across pipelines.
- Establish monitoring, alerting, logging, and operational support mechanisms.
- Ensure reliable execution of scheduled and dependency-driven data workflows.
- Troubleshoot production issues and implement corrective and preventive measures.
- Maintain data integrity, consistency, performance, and availability across integrated systems.

Experience Requirements:

- 8+ years of enterprise software engineering experience.
- 5+ years of hands-on Azure Data Engineering experience.




- 5+ years of practical experience developing and supporting Azure Data Factory solutions.
- Strong experience designing and implementing enterprise ETL/ELT pipelines using Azure cloud services.
- Proven experience developing enterprise reporting and analytics solutions using Power BI.
- Hands-on experience with Azure SQL, T-SQL, database development, and performance optimization.
- Experience integrating ERP systems, relational databases, APIs, and enterprise applications.
- Experience with Dynamics 365 Finance & Operations integration is preferred.

Mandatory Technical Skills:

- Azure Data Factory: Pipelines, mapping data flows, triggers, linked services, datasets, integration runtimes, parameterization, reusable frameworks, orchestration, and monitoring.
- Azure SQL: Database design, T-SQL, stored procedures, views, indexing, query optimization, and performance tuning.
- ETL/ELT Engineering: Data ingestion, transformation, incremental loading, CDC, data validation, reconciliation, and error handling.
- Power BI: Datasets, semantic models, dashboards, reports, data modeling, and performance optimization.
- Data Modeling: Star schemas, dimensional modeling, and reporting data marts.
- Enterprise Integration: Azure Data Lake, APIs, ERP systems, databases, and external data sources.

Preferred Skills:

- Dynamics 365 Finance & Operations data integration.
- Metadata-driven and configuration-based data engineering frameworks.
- Enterprise data warehouse modernization and optimization.
- Production monitoring, troubleshooting, and operational support for data platforms.

Ideal Candidate Profile:

The ideal candidate is an experienced Azure Data Engineer with strong hands-on development capabilities across Azure Data Factory, Azure SQL, and Power BI. They should be comfortable designing reusable data integration frameworks, optimizing enterprise data workloads, integrating complex source systems, and delivering reliable analytics solutions in a production environment.

📌 Senior Azure Data Engineer (India)
🏢 Hanker Analytics
📍 India