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Master Data Jobs in Virginia (NOW HIRING)

advansix

Data Architect

Chester, VA

$118K - $178K/yr

Ensure alignment of curated and semantic data products with master data strategy and KPI canon. Integration and Data Product Design * Define architectural patterns for ingesting and harmonizing data ...

Key Choice Group

Senior Data Engineer/Architect

Richmond, VA · On-site

$61.75 - $82.75/hr

Researches new technologies while keeping up-to-date with technological developments in relevant areas of Data Governance, Master Data, and Data Quality Desired Skills/Experience * Previous ...

ValidaTek, Inc.

Data Architect

Quantico, VA · Hybrid

$130K - $165K/hr

Lead Data Governance, Data Security, Master Data Management (MDM), Metadata Management, and Data Quality initiatives. * Define how data is stored, integrated, accessed, consumed, and managed across ...

ValidaTek

Data Architect

Quantico, VA · On-site

$68.75 - $88.50/hr

Lead Data Governance, Data Security, Master Data Management (MDM), Metadata Management, and Data Quality initiatives. * Define how data is stored, integrated, accessed, consumed, and managed across ...

Neevsys LLC

Data modeling & architecture SME

Vienna, VA · On-site

$120 - $180/hr

Data governance, master data management, or metadata management. * Modeling tools (erwin, ER/Studio, or similar). * Cloud data architecture (Azure Synapse, Snowflake, or similar). #J-18808-Ljbffr

ValidaTek

Data Architect with Security Clearance

Quantico, VA · On-site

$68.75 - $88.50/hr

Lead Data Governance, Data Security, Master Data Management (MDM), Metadata Management, and Data Quality initiatives. * Define how data is stored, integrated, accessed, consumed, and managed across ...

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Master Data information

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How much do master data jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for master data in Virginia is $43.97, according to ZipRecruiter salary data. Most workers in this role earn between $30.29 and $54.81 per hour, depending on experience, location, and employer.

What is a master data professional?

Master Data professionals are specialists who manage, maintain, and ensure the accuracy of an organization's core data assets, such as customer, product, supplier, and employee information. They play a vital role in establishing data standards, improving data quality, and supporting business processes by keeping key data consistent and reliable across systems. Their work helps organizations make better decisions, comply with regulations, and operate efficiently.

What are some common challenges faced by professionals in master data roles, and how can they be effectively managed?

One common challenge in Master Data roles is ensuring data consistency and accuracy across multiple systems and departments. Data discrepancies can arise due to varying data entry standards or system integrations, making it essential to implement robust data governance processes. Collaboration with IT, business analysts, and end users is often required to establish clear data ownership, standardization practices, and validation routines. Regular audits and continuous communication across teams help maintain high data quality and prevent errors from propagating throughout the organization.

What are the key skills and qualifications needed to thrive as a master data specialist, and why are they important?

To thrive as a Master Data Specialist, you need strong analytical skills, attention to detail, and a background in data management or information systems, often supported by a relevant degree. Familiarity with ERP systems like SAP or Oracle, data governance frameworks, and certifications such as CDMP are typically valued. Excellent communication, problem-solving, and organizational skills help you collaborate effectively and resolve data issues. These skills ensure accurate, consistent, and reliable data, which is critical for organizational decision-making and operational efficiency.

What is the difference between Master Data vs Data Analyst?

AspectMaster DataData Analyst
Required CredentialsBachelor's degree in Business, IT, or related fields; certifications like CDMP are commonBachelor's degree in Statistics, Mathematics, or related fields; certifications like CAP or Microsoft Data Analyst are common
Work EnvironmentData management teams, IT departments, enterprise systemsBusiness units, analytics teams, reporting environments
Employer & Industry UsageUsed across industries for maintaining consistent core dataUsed across industries for insights, reporting, and decision-making

Master Data professionals focus on maintaining and managing the core data that supports business operations, ensuring data accuracy and consistency. Data Analysts interpret and analyze data to generate insights and support decision-making. While both roles work with data, Master Data roles are more data governance-oriented, whereas Data Analysts focus on data analysis and reporting.

What are the most commonly searched types of Master Data jobs in Virginia? The most popular types of Master Data jobs in Virginia are:
What are popular job titles related to Master Data jobs in Virginia? For Master Data jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Master Data jobs in Virginia look for? The top searched job categories for Master Data jobs in Virginia are:
What cities in Virginia are hiring for Master Data jobs? Cities in Virginia with the most Master Data job openings:
Master Data jobs near you
Infographic showing various Master Data job openings in Virginia as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 11% Part Time, and 8% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $91,456 per year, or $44 per hour.

Data Architect

advansix

Chester, VA

$118K - $178K/yr

Full-time

Re-posted 6 days ago

AdvanSix rating

7.1

Company rating: 7.1 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

70th of 100 rated chemical manufacturers

Job description

The Data Architect defines and governs the target-state architecture for AdvanSix’s Unified Data Layer, ensuring that data across SAP, OT, lab, logistics, HSE, finance, and commercial domains is structured, integrated, and modeled for scale, trust, and reuse. This role owns the architectural blueprints, canonical data models, semantic design standards, integration patterns, and data product design principles that guide engineering delivery across the enterprise. The Data Architect partners closely with the AI, Automation, and Data team to ensure that what gets built is coherent, secure, and business-ready.

Core Responsibilities:

Enterprise Data Architecture

  • Define and maintain the target-state architecture for the Unified Data Layer, including landing, curated, and semantic layers, domain boundaries, and consumption patterns for BI, APIs, AI, and automation.
  • Develop architecture principles for modularity, interoperability, reusability, and governance across business and operational data domains.
  • Serve as the design authority for major data platform and integration decisions.

Canonical Data Modeling

  • Design enterprise and domain-level canonical models for key entities such as material, product, asset, equipment, work order, batch, vendor, customer, cost center, logistics shipment, quality event, and energy usage.
  • Define standards for dimensional modeling, semantic modeling, event models, and reference data structures that support Power BI, AI, and operational decision-making.
  • Ensure alignment of curated and semantic data products with master data strategy and KPI canon.

Integration and Data Product Design

  • Define architectural patterns for ingesting and harmonizing data from SAP S4 HANA, SAP DataSphere, historians, LIMS, TMS, HSE systems, and other enterprise platforms into the Unified Data Layer.
  • Establish standards for data contracts, schema evolution, surrogate keys, versioning, partitioning, and semantic publication.
  • Ensure that certified datasets and APIs are designed for downstream use by Reporting and BI, machine learning, Power Platform, and Copilot agents.

Architecture Governance and Design Review

  • Lead design reviews for new data products, major source integrations, and semantic layer changes.
  • Approve architectural patterns and ensure alignment with security, lineage, quality, retention, and access standards.
  • Partner with Data Strategy and AI Governance to operationalize architecture guardrails into delivery standards.

Collaboration with Engineering and OT

  • Work with the OT Data Integration Lead to ensure plant data models, asset hierarchies, event frames, and OT schemas fit the enterprise architecture without taking over OT connectivity operations.
  • Work with Big Data Engineers to translate architecture standards into implementable pipeline, storage, and semantic design patterns.
  • Partner with the Manager, Unified Data Platform and AI Engineering on platform roadmap, architecture decisions, and technical debt prioritization.

Documentation and Enablement

  • Produce architecture diagrams, conceptual and logical data models, reference patterns, and design standards.
  • Create reusable templates and guidance for engineers, analysts, and vendors.
  • Help stakeholders understand how data should be structured and consumed across the enterprise.

Basic Qualifications:

  • Minimum 8 years' of experience in enterprise data architecture, data modeling, and large-scale data platform design.
  • Proven experience designing lakehouse or enterprise data platform architectures across multiple domains.
  • Strong expertise in conceptual, logical, and physical data modeling, dimensional modeling, semantic layer design, and canonical data structures.
  • Strong understanding of Azure-based data architectures, including Databricks or Fabric and Synapse, ADLS or OneLake, Data Factory or pipelines, and integration with Power BI.
  • Working knowledge of SAP S4 HANA data structures and SAP DataSphere semantic concepts.
  • Familiarity with OT and industrial data patterns, including historians, event frames, asset hierarchies, time-series data, and ISA-based structures.
  • Strong knowledge of data contracts, schema versioning, lineage, master data alignment, and architecture governance.
  • Excellent communication skills with the ability to translate architecture into clear implementation guidance.

Preferred Qualifications

  • Experience in manufacturing, chemicals, process industries, or industrial operations.
  • Familiarity with TMS, LIMS, HSE, maintenance, and finance data domains.
  • Experience with lineage and catalog tooling, master data design, and KPI canon alignment.
  • Exposure to API-enabled data product design for AI agents and automation.
  • Lean or Six Sigma mindset and comfort working in cross-functional transformation programs.

The base salary range for this position is $118,800 to $178,200 annually.

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