Data Architect

Delta Star•Lynchburg, VA

20d

About The Position

Delta Star Inc. is seeking a strategic and hands‑on Data Architect to establish and evolve our enterprise data foundation. This role will simplify and structure data across sales, operations, supply chain, finance, engineering, and other business functions—enabling reliable reporting, scalable analytics, and data‑driven decision‑making. If you enjoy building data ecosystems, reducing complexity, and driving modern data capabilities, we want to hear from you! As a Data Architect, you will define and implement a scalable data architecture that supports enterprise reporting, analytics, and operational efficiency. You’ll assess current systems, establish standards, design data models, and partner with business and technical teams to create a more unified, accessible, and actionable data environment. Your work will directly support continuous improvement, automation, and self‑service analytics across the organization. A Day in the Life Your day may include evaluating data across ERP, CRM, and other systems, designing data models and semantic layers, or collaborating with Finance, Operations, and Engineering teams to define reporting needs. You’ll analyze existing tools, simplify data flows, and develop a roadmap for future-state data platforms. From improving data quality to mentoring analysts and aligning with IT security, you’ll balance strategic planning with hands‑on execution to drive enterprise‑wide data maturity.

Requirements

Bachelor’s degree in Information Systems, Computer Science, Data Analytics, Engineering, or related field.
7–10 years of progressive experience in data architecture, data engineering, business intelligence, or enterprise analytics.
Experience designing enterprise data models, integration solutions, and reporting architectures.
Experience working with ERP, CRM, and operational/financial systems (manufacturing or industrial environment preferred).
Experience implementing data governance, data quality, and master data management practices preferred.
Experience supporting enterprise analytics and self‑service reporting environments.
Experience evaluating or implementing cloud or hybrid data platforms preferred.
Strong understanding of data architecture principles, modeling, and integration methodologies.
Knowledge of data governance, quality, metadata management, and lifecycle practices.
Ability to translate complex business requirements into practical data solutions.
Strong analytical, problem‑solving, and organizational skills.
Ability to manage multiple initiatives and priorities effectively.
Excellent communication skills across technical and non‑technical audiences.
Familiarity with modern analytics tools, including Microsoft data platforms preferred.
Understanding of role‑based security, data privacy, and compliance standards.
Strong collaboration and stakeholder influence skills.
Ability to balance strategic thinking with hands‑on technical execution.
Ability to mentor and guide analysts and team members.

Nice To Haves

manufacturing or industrial environment preferred
data governance, data quality, and master data management practices preferred
evaluating or implementing cloud or hybrid data platforms preferred
modern analytics tools, including Microsoft data platforms preferred

Responsibilities

Assess, document, and inventory enterprise data sources, integrations, and reporting dependencies.
Define current‑state and target‑state data architecture, including integration patterns and phased roadmap.
Establish and enforce enterprise data standards (modeling, naming conventions, structures, metadata, and documentation).
Design and implement scalable data models, curated datasets, and semantic layers for reporting and analytics.
Evaluate and rationalize data tools and reporting platforms to reduce redundancy and complexity.
Develop and maintain a roadmap for data platform evolution, including modern cloud and hybrid technologies.
Define and implement data governance practices, including ownership, quality validation, and issue resolution.
Partner with business units to establish system‑of‑record definitions and trusted data sources.
Improve data pipelines and integration capabilities with technical teams.
Identify opportunities to consolidate reporting tools and enhance self‑service analytics capabilities.
Develop and execute data quality strategies, monitoring processes, and continuous improvement initiatives.
Define standards for secure data access, privacy, retention, and compliance.
Collaborate with IT security to align data practices with cybersecurity and regulatory requirements.
Communicate data strategies, roadmaps, and priorities to leadership and stakeholders.
Provide technical guidance and mentorship to analysts and team members.
Support ongoing enhancements to enterprise reporting and analytics capabilities.