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# Azure Data Engineer

- **Company:** RIVAGO INFOTECH INC.
- **Location:** McLean, VA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** .NET Framework, Microsoft Azure, C Sharp (Programming Language), Computer Programming, Continuous Integration, Data Validation, Data Integration, Extract Transform Load (ETL), Data Security, Relational Databases, Database Development, DevOps, SQL Azure, Query Optimization, SQL Stored Procedures, SQL Databases, Freeform SQL, Azure Data Factory, Snowflake, Indexer, Backend, Git, Data Lakes, Deployment Automation, Star Schema, Azure Synapse Analytics, Data Pipelines
- **Published:** May 20, 2026
- **Apply:** https://www.dice.com/job-detail/edded6c4-60d1-4df4-9051-cb8215878a31

## About the Role

* 8+ years of professional experience as a Data Engineer or similar role.
 * Strong programming skills in .NET / C# for backend or data integration components.
 * Deep expertise in SQL including query optimization, indexing, stored procedures, and relational database concepts.
 * Proven experience building ETL pipelines and data workflows.
 * Hands-on experience with Azure Data Factory / Azure Data Pipelines (ADT) (heavy/advanced experience required).
 * Knowledge of Azure storage services such as Azure SQL DB, Synapse, Data Lake Storage (ADLS), Blob Storage.
 * Familiarity with CI/CD pipelines, Git, and deployment automation.
 * Understanding of data modeling concepts (star schema, snowflake, SCD, normalization).

## Description

* Design, develop, and maintain scalable data pipelines using Azure Data Factory / Azure Data Pipelines (ADT).
 * Build and optimize ETL workflows to extract, transform, and load data from multiple structured and unstructured sources.
 * Develop data integration services and backend components using .NET (C#).
 * Write and optimize complex SQL queries, stored procedures, and performance-tuned database solutions.
 * Implement data quality checks, validation frameworks, and monitoring dashboards.
 * Work with cross-functional teams (Data Analysts, Architects, DevOps) to understand data needs and deliver robust solutions.
 * Ensure data security, compliance, and governance across pipelines and storage layers.
 * Troubleshoot data pipeline issues and drive root-cause analysis and resolutions.
 * Contribute to architecture discussions and recommend improvements for performance, scalability, and cost efficiency.


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