Data Architect Supervisor

Zeiders Enterprise•Woodbridge, VA

About The Position

The Data Architect Supervisor is a full-time employee of Zeiders Enterprises, Inc. responsible for designing, developing, managing, and continuously improving the organization's enterprise data architecture and data technology environment. This hands-on leadership role establishes a scalable, secure, and reliable data foundation for business operations, reporting, analytics, automation, and emerging AI capabilities. The position works with IT, business leaders, cybersecurity, finance, human resources, and other stakeholders to make data accessible, accurate, secure, governed, and actionable, and develops related data policies, procedures, and technical controls. The role leads enterprise data architecture and technology management, data engineering and integration, governance and quality, security and compliance, business intelligence and AI enablement, project and stakeholder management, and supervision of data staff. It combines strategic planning and team leadership with hands-on technical work across data architecture, engineering, database administration, integration, and problem resolution.

Requirements

Bachelor’s degree in computer science, Information Systems, Data Science, Engineering, or a related field.
At least 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.
Strong understanding of data modeling, data governance, data quality, metadata management, security, and lifecycle management.
Strong analytical, problem-solving, communication, and stakeholder management skills.
Ability to lead, mentor, and develop data professionals; set priorities and expectations, assign work, and foster collaboration and accountability.
Ability to establish a practical data technology strategy while remaining hands-on with architecture, engineering, and problem resolution.
Ability to understand data flows across applications, business processes, programs, and organizational functions.
Understanding of security, compliance, contractual, and data protection requirements associated with government contracting.
Ability to translate business requirements into practical data solutions and communicate technical concepts effectively to business leaders.
Demonstrated ability to carry work from strategy and architecture through implementation, operationalization, and continuous improvement.

Nice To Haves

Experience with data orchestration tools such as Kafka, FiveTran, and dbt.
Experience supporting a government contractor or federal government organization.
Experience 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.

Responsibilities

Develop and maintain enterprise data architecture spanning data sources, databases, warehouses, lakes, integrations, APIs, and reporting platforms.
Design scalable data solutions for operational systems, business intelligence, analytics, automation, and AI initiatives.
Evaluate, select, implement, and manage data technologies and platforms; establish architecture standards, patterns, principles, and technology roadmaps.
Assess the existing data environment and develop a multi-year modernization and optimization roadmap; identify opportunities to consolidate, integrate, automate, and improve data systems.
Perform hands-on data engineering, database administration, integration, and architecture work as appropriate; monitor performance, capacity, availability, and reliability.
Design and implement data pipelines and ETL/ELT processes integrating enterprise applications and external sources.
Develop and maintain data models for operational reporting, analytics, and business intelligence; establish integration patterns across applications, databases, cloud services, and other sources.
Ensure pipelines are reliable, documented, monitored, and secured; troubleshoot complex data, integration, and performance issues.
Support development and maintenance of data warehouses, data marts, and analytical environments.
Establish and maintain data governance practices, standards, policies, and procedures, including data ownership, stewardship, classification, retention, and lifecycle requirements.
Develop data quality processes and maintain data dictionaries, metadata repositories, business glossaries, and lineage documentation; partner with stakeholders on authoritative data sources and common definitions.
Promote data as an enterprise asset and establish appropriate controls around its use.
Align data architecture and solutions with government contracting, cybersecurity, privacy, and compliance requirements; support protection of CUI, PII, and other sensitive information.
Collaborate with cybersecurity and infrastructure teams on access controls, encryption, monitoring, logging, and data protection; support applicable contractual, regulatory, organizational, and NIST-based controls.
Ensure appropriate data segregation, access, retention, and handling in government and commercial environments; participate in security assessments, risk reviews, technology evaluations, and compliance activities.
Partner with business and technology teams to establish a reliable data foundation for reporting and analytics; support dashboards, management reporting, operational metrics, and executive analytics.
Enable data solutions for automation, machine learning, and AI; establish standards for data preparation and accessibility for analytics and AI use cases.
Identify opportunities to use data to improve operational efficiency, customer experience, program performance, and decision-making.
Work with executives, program managers, business leaders, and technical teams to gather data requirements and translate them into technology solutions.
Lead or contribute to data technology projects and strategic initiatives; develop project plans, technical requirements, architecture documentation, and implementation approaches.
Communicate technical concepts to technical and non-technical stakeholders; manage relationships with data vendors and service providers.
Participate in technology planning, budgeting, procurement, and vendor evaluations.
Directly supervise data analysts, engineers, and other support staff as assigned; handle employee selection, onboarding, coaching, performance management, disciplinary actions, and professional development.
Lead and oversee data team operations; set team priorities, objectives, and performance expectations, assign work, and establish professional development plans.
Set standards for documentation, development, testing, deployment, and operational support; foster collaboration, accountability, knowledge sharing, and continuous development across the data team and other functions.
Balance strategic responsibilities with hands-on technical execution and guide initiatives from strategy and architecture through implementation, operationalization, and continuous improvement.