Data Architect – Enterprise Applications
Role Purpose
The Data Architect is responsible for defining, governing, and evolving enterprise data architecture across ERP, operational systems, and analytics platforms. This role ensures data consistency, scalability, and integrity as the organization executes ERP implementations and operating-company rollouts.
This position does not perform day-to-day reporting or operational data fixes. Instead, it defines the data structures, standards, and architectural guardrails that other teams operate within.
Key Responsibilities
Data Architecture & Design
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Define and maintain enterprise data models across ERP, operational, and analytics platforms.
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Design canonical data models for core domains including customers, vendors, jobs, projects, financials, and assets.
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Define data relationships and ownership across core operational systems, ERP finance platforms, and downstream analytics solutions.
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Establish standards for master data, reference data, and transactional data.
Data Governance & Quality
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Define data ownership, stewardship, and accountability by domain.
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Establish data quality rules, validation standards, and reconciliation frameworks.
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Partner with application and operations leaders to align system configuration with enterprise data standards.
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Define auditability and traceability standards for financial and operational data.
Integration & Analytics Enablement
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Partner with integration engineers to define data contracts, schemas, and transformation rules.
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Ensure data models support reporting, BI, and downstream analytics use cases.
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Review and approve data design decisions for new integrations and ERP modules.
ERP & Implementation Support
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Support ERP implementations by validating data design, mappings, and cutover readiness.
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Review data migration strategies to ensure alignment with target-state architecture.
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Provide architectural guidance during fit-gap analysis, design, and testing phases.
Required Qualifications
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5+ years of experience designing enterprise data models in ERP and operational environments.
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7+ years of hands-on experience with relational databases and modern analytics platforms.
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Proven experience defining data standards, governance models, and data ownership frameworks.
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5+ years of experience supporting ERP implementations and system integrations.
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Strong ability to translate business processes into logical and physical data models.
Preferred Qualifications
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Experience in construction, field services, or project-based ERP environments.
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Experience supporting multi-entity and multi-ERP rollouts.
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Familiarity with data lakes, data warehouses, and modern BI stacks.
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Experience working with integration platforms and event-based or API-driven architectures.
Success Measures
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Clearly defined and adopted enterprise data models.
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Reduced data inconsistencies across systems.
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Faster, cleaner data migrations and ERP cutovers.
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Improved trust in financial and operational reporting.
Determining compensation for this role (and others) at Vaco/Highspring depends upon a wide array of factors including but not limited to the individual’s skill sets, experience and training, licensure and certifications, office location and other geographic considerations, as well as other business and organizational needs. With that said, as required by local law in geographies that require salary range disclosure, Vaco/Highspring notes the salary range for the role is noted in this job posting. The individual may also be eligible for discretionary bonuses, and can participate in medical, dental, and vision benefits as well as the company’s 401(k) retirement plan. Additional disclaimer: Unless otherwise noted in the job description, the position Vaco/Highspring is filing for is occupied. Please note, however, that Vaco/Highspring is regularly asked to provide talent to other organizations. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. Submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. Further assessment of candidates beyond this initial phase within Vaco/Highspring will be otherwise assessed by recruiters and hiring managers. Vaco/Highspring does not have knowledge of the tools used by its clients in making final hiring decisions and cannot opine on their use of AI products.