
11 - 50 employees
ποΈ Government
π Cybersecurity
πΌ Consulting
Government β’ Cybersecurity β’ Consulting
Imagineeer is a mission-focused consultancy that helps U. S. government agencies modernize systems and deploy AI safely. Imagineeer builds shared, scalable, production-ready interoperability layers between policy, data, and operations so agencies can move from pilots to production while maintaining security, compliance, and governance. They offer AI-ready cloud and Zero Trust engineering, legacy system transformation, data intelligence and digital stewardship, cybersecurity including post-quantum security, and mission operations support. They operate ImagineLabs as a co-creation environment for agencies to test workflows with real data and validate governance. Headquartered in Arlington, Virginia, they emphasize leaders with inside federal experience and focus on federal domains like health, defense, homeland security, and transportation.
π₯ 2 hours ago
βοΈ Virginia β Remote
π΅ $130k - $135k / year
β° Full Time
π‘ Mid-level
π Senior
π° Data Engineer
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11 - 50 employees
ποΈ Government
π Cybersecurity
πΌ Consulting
Government β’ Cybersecurity β’ Consulting
Imagineeer is a mission-focused consultancy that helps U. S. government agencies modernize systems and deploy AI safely. Imagineeer builds shared, scalable, production-ready interoperability layers between policy, data, and operations so agencies can move from pilots to production while maintaining security, compliance, and governance. They offer AI-ready cloud and Zero Trust engineering, legacy system transformation, data intelligence and digital stewardship, cybersecurity including post-quantum security, and mission operations support. They operate ImagineLabs as a co-creation environment for agencies to test workflows with real data and validate governance. Headquartered in Arlington, Virginia, they emphasize leaders with inside federal experience and focus on federal domains like health, defense, homeland security, and transportation.
β’ Assess and inventory existing legacy data in application data stores, shared folders and shared drives. β’ Assess the quality, completeness, and relevance of data to be migrated. β’ Identify and document data dependencies, redundancies, and inconsistencies. β’ Collaborate with stakeholders to understand data structures, relationships, and required formats for successful migration. β’ Develop a comprehensive data migration plan that outlines steps, timelines, and resource requirements for the migration process. β’ Identify potential challenges and propose solutions to mitigate risks associated with data migration. β’ Interpret legacy APIs and other system integrations, and define mapping between systems. β’ Plan for thorough testing of the migrated data to ensure accuracy, completeness, and successful integration. β’ Recommend validation reports and the process to document any discrepancies and work closely with stakeholders to resolve issues. β’ Collaborate with software engineers, database administrators, and development teams to ensure compatibility and alignment with the overall architecture. β’ Maintain effective communication with project stakeholders to provide updates on migration planning progress and gather feedback. β’ Create and maintain technical documentation related to planned data migration processes, procedures, and system configurations. β’ Specify reports on migration progress, data quality metrics, and issue resolution.
β’ Bachelorβs degree in Computer Science, Information Technology, Data Science, or a related field. β’ Previous experience as a Database Engineer and proven experience in data migration, particularly with legacy systems and cloud environments. β’ Proficiency in data migration tools and ETL processes (e.g., Talend, Informatica, SSIS, or similar). β’ Strong knowledge of database management systems (e.g., SQL Server, Oracle, MySQL, PostgreSQL). β’ Experience with scripting languages (e.g., Python, Perl, SQL, PowerShell) for data transformation and automation. β’ Familiarity with indexing and data accessibility in software applications.
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