• build and monitor robust ETL/ELT pipelines using BigQuery, Dataflow, and Cloud Composer • develop high-performance SQL scripts for complex data transformations • contribute to the design and refinement of data models • proactively identify and resolve bottlenecks in data pipelines • partner with Data Analysts and stakeholders to translate business logic • participate in peer code reviews and maintain documentation

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.

• Support enterprise data platform initiatives • Manage and implement changes across enterprise data environments including Azure Synapse and Databricks • Support ETL processes, data pipelines, and API connectivity • Ensure data consistency, quality, and accessibility • Develop and maintain scalable data pipelines and integration services • Collaborate with data architects, analysts, and business stakeholders to support data integration and master data initiatives.

• Support the design, discovery, and implementation of enterprise data platforms that enable advanced analytics and operational workflows. • Lead the development of a centralized data storefront and enterprise analytics ecosystem. • Integrate enterprise data into operational workflows. • Develop and maintain scalable data architectures, pipelines, and data integration frameworks. • Integrate multiple structured and unstructured data sources from enterprise systems, operational databases, and external platforms. • Ensure data architectures support data governance, lineage, quality monitoring, and enterprise data management standards. • Lead technical discovery sessions with mission and business stakeholders to identify data sources, use cases, and operational requirements. • Develop analytics dashboards, operational insights, and data products supporting leadership decision-making. • Provide technical leadership in data architecture design and integration strategies.