Data Architect Supervisor

The Data Architect Supervisor works as a full-time employee of Zeiders Enterprises, Inc. (Zeiders) and is responsible for designing, developing, managing, and continuously improving the organization’s enterprise data architecture and data technology environment. This position plays a hands‑on role in establishing a scalable, secure, and reliable data foundation that enables business operations, reporting, analytics, automation, and emerging AI capabilities.

The Data Architect Supervisor will actively engage in technical work. The ideal candidate is both a strategic thinker and hands‑on technologist who can translate business requirements into practical data solutions and establish the standards, processes, and technologies necessary to support a data‑driven organization. They will work closely with IT, business leaders, cybersecurity, finance, human resources, and other stakeholders to ensure that data is accessible, accurate, secure, governed, and actionable.

They will be responsible for the development of data policies, procedures, and technical controls.

• Develop and maintain the organization’s enterprise data architecture, including data sources, databases, data warehouses, data lakes, integrations, APIs, and reporting platforms.
• Design scalable data solutions that support operational systems, business intelligence, analytics, automation, and AI initiatives.
• Evaluate, select, implement, and manage data technologies and platforms.
• Establish data architecture standards, patterns, principles, and technology roadmaps.
• Assess the current data environment and develop a multi-year roadmap for modernization and optimization.
• Identify opportunities to consolidate, integrate, automate, and improve the organization’s data environment.
• Maintain hands‑on responsibility for data engineering, database administration, data integration, and architecture activities as appropriate.
• Monitor data technology performance, capacity, availability, and reliability.
• Design and implement data pipelines and ETL/ELT processes to integrate data from enterprise applications and external sources.
• Develop and maintain data models supporting operational reporting, analytics, and business intelligence.
• Establish integration patterns for connecting applications, databases, cloud services, and other data sources.
• Ensure data pipelines are reliable, documented, monitored, and appropriately secured.
• Troubleshoot complex data, integration, and performance issues.
• Support the development and maintenance of data warehouses, data marts, and analytical environments.

• Establish and maintain data governance practices, standards, policies, and procedures.
• Define data ownership, stewardship, classification, retention, and lifecycle requirements.
• Develop processes for monitoring and improving data quality, completeness, accuracy, consistency, and timeliness.
• Establish and maintain data dictionaries, metadata repositories, business glossaries, and data lineage documentation.
• Partner with business stakeholders to define authoritative sources of data and establish common data definitions.
• Promote data as an enterprise asset and establish appropriate controls around its use.

• Ensure data architecture and solutions align with applicable government contracting, cybersecurity, privacy, and compliance requirements.
• Support the protection of Controlled Unclassified Information (CUI), Personally Identifiable Information (PII), and other sensitive organizational information.
• Collaborate with cybersecurity and infrastructure teams to implement appropriate access controls, encryption, monitoring, logging, and data protection…