Role Description

The Lead Azure Data Engineer is responsible for migration, governance, and data integration for the implementation of new Microsoft Cloud based document routing and task management system. They will ensure alignment with the technical, security, and document management requirements such as:

• Leading data discovery and mapping
• Validating metadata standards
• Managing data migration into Dataverse and SharePoint Online
• Ensuring proper implementation of retention, auditability, and role-based access controls within the Microsoft SaaS architecture

Qualifications

• A minimum of 6 years IT experience with focus on data integration and data migration using Azure Data Services
• Must have strong experience designing data models, configuring Dataverse tables, managing relationships, enforcing row- and field-level security, and supporting workflow-driven data structures
• Knowledge of SharePoint Online document libraries, metadata schemas, retention labels, records management, and large-volume document storage design
• Proficiency in data mapping, transformation, validation, and migration using APIs, Azure services, Power Automate, and REST-based integrations
• Experience with Azure data services (e.g., Azure Data Factory, Azure SQL, Azure AI Search, Azure storage components) in FedRAMP-aligned environments
• Understanding of producing audit logging, identity integration (Entra ID), and support for records retention and legal hold requirements
• Ability to structure data for Power BI dashboards, performance reporting, and AI-enabled search and discovery
• Establishing metadata standards, validation rules, lifecycle controls, and ensuring data accuracy and consistency across enterprise workflows
• Bachelors degree or equivalent
• Must be a US Citizen

Requirements

• Microsoft Azure data services certifications
• Active Federal Government Public Trust clearance

Benefits

The projected compensation range for this position is $135K - $160K annualized (USD). The final salary offered will generally fall within this range and is determined by various factors, including but not limited to the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as internal pay equity, location, contract-specific affordability and other organizational requirements.