Senior Azure Data Migration & Dataverse Integration Engineer in Baltimore

Seeking a Senior Azure Data Migration & Dataverse Integration Engineer to design, develop, implement, and support enterprise data migration and synchronization capabilities between Microsoft SQL Server and Microsoft Dataverse., The position requires a senior hands-on engineer capable of owning the complete data pipeline lifecycle, including source analysis, data mapping, extraction, transformation, migration, synchronization, validation, exception handling, monitoring, performance optimization, and automated deployment., The engineer will develop and maintain repeatable pipelines supporting initial bulk migration, incremental migration, Change Data Capture (CDC), ongoing synchronization, and transition/cutover activities between legacy SQL Server applications and modern Microsoft Power Platform/Dataverse solutions., The engineer must understand the risks associated with bidirectional synchronization, including update conflicts, synchronization loops, transaction ordering, and determination of the authoritative system of record., Legacy SQL Server * Extraction * Staging/Bronze * Validation/Transformation * Silver * Business Rules/Mapping * Gold/Target-Ready Data * ADF Load Pipeline * Dataverse * Reconciliation, Develop operational capabilities to monitor migration and synchronization processing, including, The engineer must be capable of working directly with application developers, Power Platform developers, database administrators, solution architects, business analysts, and system owners to determine how legacy data will be migrated, synchronized, validated, and ultimately transitioned from the legacy environment.

The engineer should be capable of developing reusable, metadata-driven pipeline patterns rather than creating independent hard-coded pipelines for every table., The candidate should be capable of implementing a controlled migration architecture such as, * 7+ years of data engineering, database development, integration, or data migration experience. \n

• 4+ years of Microsoft Azure data engineering experience. \n

• Advanced Azure Data Factory development experience. \n

• Advanced Microsoft SQL Server and T-SQL experience. \n

• Strong Microsoft Dataverse experience. \n

• Experience migrating enterprise SQL data into Dataverse. \n

• Experience with CDC, incremental loads, delta processing, and synchronization. \n

• Experience developing ETL/ELT pipelines. \n

• Experience with REST APIs and Dataverse Web API. \n

• Experience with Azure SQL. \n

• Experience with Azure Key Vault and Managed Identities. \n

• Experience with Azure DevOps source control and pipelines. \n

• Experience implementing automated data validation and reconciliation. \n

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Technical Experience, The successful candidate must be able to independently take a legacy SQL data requirement through the complete technical lifecycle

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• Design and implement end-to-end SQL Server-to-Dataverse data migration pipelines. \n

• Develop automated pipelines using Azure Data Factory (ADF) and supporting Azure services. \n

• Analyze legacy SQL Server databases, tables, views, relationships, stored procedures, and data dependencies. \n

• Map legacy SQL Server data structures to Dataverse tables, columns, relationships, choices, lookups, and alternate keys. \n

• Develop repeatable processes for: \n

• Initial/bulk data migration \n

• Incremental data migration \n

• Change Data Capture \n

• Delta processing \n

• Scheduled synchronization \n

• Near-real-time synchronization \n

• Legacy-to-Dataverse synchronization \n

• Dataverse-to-legacy synchronization where required \n

• Cutover and final synchronization \n

• Develop and maintain ADF pipelines, datasets, linked services, integration runtimes, triggers, parameters, variables, and reusable pipeline components. \n

• Develop transformation and data-cleansing logic required to convert legacy data into Dataverse-compatible structures. \n

• Implement controlled sequencing to maintain parent/child relationships and referential integrity. \n

• Develop lookup resolution and cross-reference processes for Dataverse GUIDs and legacy SQL identifiers. \n

• Implement restartable and recoverable migration processes. \n

• Develop pipeline logging, audit, exception handling, retry, and reconciliation capabilities. \n

• Validate migrated data for completeness, accuracy, integrity, and consistency. \n

• Perform source-to-target record-count and field-level reconciliation. \n

• Troubleshoot failed records, pipeline failures, API limitations, data-quality issues, and performance problems. \n

• Develop automated deployment processes for data pipeline components across DEV, TEST, UAT, and PROD environments. \n

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Azure Data Factory / Pipeline Responsibilities

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The candidate must have advanced hands-on experience designing and developing Azure Data Factory solutions.

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