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# Azure Data Architect

- **Company:** Lorven Technologies Inc
- **Location:** McLean, VA, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Microsoft Azure, Data Architecture, Data Cleansing, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Security, Data Warehousing, DevOps, Python (Programming Language), SQL Azure, Power BI, DataOps, SQL Databases, SQL Server Reporting Services, SQL Server Integration Services, Enterprise Data Management, Azure Data Factory, Informatica Powercenter, Snowflake, Databricks
- **Published:** May 21, 2026
- **Apply:** https://www.dice.com/job-detail/c4273384-e584-4bfa-be06-dccc49a0b005

## About the Role

* 12+ years in data engineering / data platform roles with architecture responsibility.
 * Strong experience with Azure data technologies (ADF, ADLS, Synapse, Azure SQL).
 * Solid understanding of ETL/ELT, data modeling, and data warehousing.
 * Experience with Power BI, exposure to SSIS / SSRS.
 * Proficiency in SQL and architectural familiarity with Python.
 * Healthcare (Payer / Provider) experience preferred.

Nice to Have:

 * Exposure to AI/ML enablement (data preparation, ML-ready architectures).
 * Snowflake or lakehouse architecture experience.

## Description

* Data Architect responsible for defining and governing Azure-based data architecture, supporting ETL modernization, analytics, and reporting, while working closely with Data Engineering, BI, and Data Science teams., * Collaborate with Solution & Enterprise Architects to translate business requirements into scalable data architecture designs.
 * Define end to end data architecture across ingestion, storage, processing, analytics, and reporting.
 * Provide architectural oversight for ETL/ELT solutions using Azure Data Factory, Databricks, Informatica, SSIS.
 * Guide ETL automation, monitoring, and DevOps/DataOps best practices (implementation by engineers).
 * Define and govern analytics & reporting architecture using Power BI, SSRS, and enterprise data models.
 * Ensure data security, governance, and PHI compliance across platforms.
 * Partner with Analytics, Reporting, Data Science, and ML teams to enable downstream use cases.
 * Participate in Agile delivery and provide architecture input during planning and design phases.


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