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# Azure Data Engineer

- **Company:** RIVAGO INFOTECH INC.
- **Location:** McLean, VA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Agile Methodology, Artificial Intelligence, Microsoft Azure, Data Architecture, Data Validation, Data Cleansing, Information Engineering, Extract Transform Load (ETL), Relational Databases, DevOps, JSON, Python (Programming Language), Microsoft SQL Server, SQL Azure, Performance Tuning, Power BI, DataOps, Simple Data Format, SQL Stored Procedures, SQL Databases, SQL Server Reporting Services, SQL Server Integration Services, Data Ingestion, Azure Data Factory, Sql Optimization, Snowflake, Pyspark, Drilldown, Data Pipelines, Databricks
- **Published:** September 25, 2026
- **Apply:** https://www.dice.com/job-detail/bb69ec93-bc18-46bd-8f44-a556719788ea

## About the Role

* 7+ years of experience in Data Engineering / BI Engineering
 * Exposure to Azure data services (ADF, ADLS, Azure SQL, Synapse)
 * Strong experience with SQL Server (or equivalent RDBMS) and advanced SQL
 * Hands-on experience with Power BI (modeling, DAX, publishing)
 * Experience with SSIS for ETL and SSRS for reporting
 * Working knowledge of Python is a plus

Nice to Have

 * Healthcare (Payer / Provider) domain experience
 * Exposure to AI/ML data preparation or analytics use cases
 * Experience with Snowflake or lakehouse architecture.

## Description

Hands-on Data Engineer responsible for building ETL/ELT pipelines and delivering reporting and BI solutions, supporting analytics and business reporting needs on Azure and SQL-based platforms., * Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory, Databricks (PySpark), SSIS, or Informatica.

 * Develop and optimize SQL queries, views, and stored procedures to support reporting and analytics.
 * Build and maintain Power BI dashboards, including data models and DAX calculations.
 * Develop and support SSRS reports (parameterized, drill-down, operational reports).
 * Handle data ingestion from multiple sources and file formats (CSV, JSON, Excel, etc.).
 * Perform data validation, reconciliation, and performance tuning.
 * Work in Agile teams and follow DevOps/DataOps best practices.
 * Ensure data quality, security, and compliance (PHI where applicable).


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