Data Architect Supervisor

Job Title: Data Architect Supervisor

Summary

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.

Essential Duties and Responsibilities

Data Architecture & Technology Management

• 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.

Data Engineering & Integration

• 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.

Data Governance & Quality

• 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.

Government Contracting & Security

• 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 mechanisms.
• Support compliance with applicable contractual, regulatory, and organizational requirements, including NIST-based security controls where applicable.
• Ensure appropriate data segregation, access, retention, and handling practices within government and commercial environments.
• Participate in security assessments, risk reviews, technology evaluations, and compliance activities as required.

Business Intelligence, Analytics & AI

• Partner with business and technology teams to establish a reliable data foundation for enterprise reporting and analytics.
• Support the development of dashboards, management reporting, operational metrics, and executive-level analytics.
• Enable data solutions supporting automation, machine learning, and AI initiatives.
• Establish standards for data preparation and accessibility for analytics and AI use cases.
• Help identify opportunities to leverage data to improve operational efficiency, customer experience, program performance, and decision-making.

Project & Stakeholder Management

• Work with executives, program managers, business leaders, and technical teams to understand data requirements and translate them into technology solutions.
• Lead or contribute to data-related technology projects and strategic initiatives.
• Develop project plans, technical requirements, architecture documentation, and implementation approaches.
• Communicate complex technical concepts to both technical and non-technical stakeholders.
• Manage relationships with data technology vendors and service providers.
• Participate in technology planning, budgeting, procurement, and vendor evaluations.

Supervisor Responsibilities

• Directly supervises data analysts, engineers and other support staff as assigned.
• Responsible for employee selection, onboarding, coaching, performance management, disciplinary actions, and professional development.
• Provides leadership and oversight of the data management team's operational activities.

Qualifications

• Bachelor's degree in computer science, Information Systems, Data Science, Engineering, or a related field.
• 8+ years of progressive experience in data architecture, data engineering, database management, business intelligence, or related technology disciplines.
• Demonstrated hands-on experience managing data technologies and enterprise data environments.
• Experience designing and implementing data architectures, data warehouses, data integration solutions, and data pipelines.
• Experience with relational databases, Python, and SQL.
• Experience with cloud-based data technologies and platforms.
• Experience developing ETL/ELT processes and integrating data from multiple systems.
• Experience working with Data orchestration tools Kafka, FiveTran, dbt, and others.
• Experience with data modeling, data governance, data quality, and metadata management.
• Experience supporting a government contractor or federal government organization.
• Experience working with CUI, NIST SP 800-171, CMMC, FedRAMP, or other government cybersecurity requirements.
• Experience with Microsoft Fabric, Azure Data Factory, Azure SQL, SQL Server, Power BI, Databricks, or similar technologies.
• Experience supporting enterprise data warehouses, data lakes, or Lakehouse architecture.
• Experience with APIs, integration platforms, and modern data architectures.
• Experience supporting AI, machine learning, or intelligent automation initiatives.
• Experience establishing or maturing an enterprise data governance program.

Other required Skills and Competencies

Team Leadership

• Lead, mentor, and develop a team of data professionals.
• Establish team priorities, objectives, performance expectations, and professional development plans.
• Assign work based on organizational priorities, technical capabilities, and project requirements.
• Establish standards for documentation, development, testing, deployment, and operational support.
• Promote collaboration between the data team and other IT and business functions.
• Balance strategic responsibilities with hands-on technical execution.
• Strong analytical, problem-solving, communication, and stakeholder management skills.

Other Required Skills and Competencies

• Technical Leadership - Ability to establish a practical data technology strategy while remaining hands-on with architecture, engineering, and problem resolution.
• Enterprise Thinking - Ability to understand how data flows across applications, business processes, programs, and organizational functions.
• Data Management - Strong understanding of data architecture, modeling, integration, quality, governance, security, and lifecycle management.
• Government & Security Awareness - Understanding of the unique security, compliance, contractual, and data protection requirements associated with government contracting.
• Team Leadership - Ability to lead a small, high-performing technical team while fostering accountability, collaboration, knowledge sharing, and continuous development.
• Business Partnership - Ability to translate business requirements into practical data solutions and communicate technical concepts effectively to business leaders.
• Execution - Demonstrated ability to move from strategy and architecture through implementation, operationalization, and continuous improvement.

Physical Demands

Works in office areas. Sits, stands, bends, lifts, and moves intermittently during working hours. Use personal computers, telephones, printers, and other office equipment. May occasionally lift and/or move up to 10 pounds. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

Work Environment

The work environment characteristics described are representative of those encountered while performing the essential functions of this job. The noise level is typically quiet. #NATIONWIDE

Compensation is based on geographic location and experience. Wages are available upon request.