MDM Analyst: Build Enterprise Data Foundations & Governance

Koch Business Solutions, LP

Tulsa (OK)

On-site

USD 70,000 - 100,000

Full time

8 days ago

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Benefits offered by this job

Medical
Dental
Vision
Retirement plan
Educational assistance
Paid time off

Job summary

Koch Engineered Solutions (KES) is seeking a Master Data Management (MDM) Analyst to design and scale enterprise data capabilities across business domains. You will work with Data Architects, Data Leads, Data Analysts, and data owners to implement SSOT governance and guardrails for trusted data.

The role is in-office in Wichita, KS or Tulsa, OK with no visa sponsorship. You will balance technical rigor with business impact, building reusable data products and durable data foundations for

Qualifications

  • Experience with or implementing an MDM platform (Reltio/Informatica/TIBCO).
  • Ability to translate business requirements into platform configuration.
  • Experience building data quality, lineage, and survivorship rules.

Responsibilities

  • Collaborate with Data Architects and Analytics Leaders to define data modeling standards and reusable patterns.
  • Partner with Data Engineers, BI Developers, and product teams to ensure usable, scalable data products.
  • Align on business definitions, domain boundaries, and data quality standards to support trusted golden records.
  • Identify data coverage gaps and prioritize improvements using a product-minded approach.
  • Design well-governed data layers to enable model training and AI insights.

Skills

MDM platforms
Security logic
Data governance
Stakeholder collaboration

Tools

Graph databases

Job description

Koch Engineered Solutions (KES) is seeking a Master Data Management (MDM) Analyst to design and scale enterprise data capabilities across business domains. You will work with Data Architects, Data Leads, Data Analysts, and data owners to implement SSOT governance and guardrails for trusted data.

The role is in-office in Wichita, KS or Tulsa, OK with no visa sponsorship. You will balance technical rigor with business impact, building reusable data products and durable data foundations for

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