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Data Taxonomy Jobs in Rochester Hills, MI (NOW HIRING)

Respond to customer concerns related to labor operation data, including vehicle application questions, estimated work-time verification, and taxonomy classification. * Quality Assurance: Execute ...

Respond to customer concerns related to labor operation data, including vehicle application questions, estimated work-time verification, and taxonomy classification. * Quality Assurance: Execute ...

Respond to customer concerns related to labor operation data, including vehicle application questions, estimated work-time verification, and taxonomy classification. * Quality Assurance: Execute ...

Respond to customer concerns related to labor operation data, including vehicle application questions, estimated work-time verification, and taxonomy classification. * Quality Assurance: Execute ...

Respond to customer concerns related to labor operation data, including vehicle application questions, estimated work-time verification, and taxonomy classification. * Quality Assurance: Execute ...

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Data Taxonomy information

What are some typical challenges faced when developing and maintaining a data taxonomy within an organization?

One common challenge when working in data taxonomy is ensuring consistency across different departments that may use varied terminology or classification standards. Data taxonomists often need to facilitate collaboration between stakeholders to agree on definitions and structures, which requires strong communication and negotiation skills. Another challenge is keeping the taxonomy up-to-date as business needs and data sources evolve, necessitating regular reviews and updates. Successfully navigating these issues helps improve data discoverability, governance, and overall business intelligence.

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

To thrive as a Data Taxonomist, you need a strong background in information science, data organization, and metadata management, often supported by a degree in library science, information systems, or a related field. Familiarity with taxonomy management tools, data modeling software, and standards such as SKOS or RDF is commonly required. Attention to detail, analytical thinking, and effective communication are essential soft skills for collaborating across teams and ensuring data consistency. These skills and qualifications are crucial for creating structured data frameworks that improve data discoverability, usability, and governance.

What is the difference between Data Taxonomy vs Data Analyst?

AspectData TaxonomyData Analyst
Primary FocusOrganizing and classifying data structuresAnalyzing data to extract insights
Skills & CertificationsData modeling, taxonomy development, data management certificationsStatistical analysis, SQL, data visualization skills
Work EnvironmentData management teams, data governance departmentsBusiness units, analytics teams
Industry UsageData governance, information architectureBusiness intelligence, reporting

Data Taxonomy involves creating structured classifications for data assets, ensuring consistency and clarity across systems. Data Analysts focus on interpreting data to support decision-making. While both roles work with data, Data Taxonomy emphasizes data organization, whereas Data Analysts analyze data for insights.

How to become a data taxonomist?

To become a data taxonomist, develop skills in data management, classification, and metadata standards, often through a degree in information science, computer science, or related fields. Gaining experience with data modeling tools, taxonomy development, and understanding domain-specific knowledge is essential, along with familiarity with data governance and relevant software such as Protégé or Excel.

What does a data taxonomy specialist do?

A data taxonomy specialist develops and maintains structured classifications of data within an organization to improve data organization, searchability, and governance. They analyze data assets, create standardized naming conventions, and often use tools like metadata management systems to ensure consistent data categorization across systems.

What skills are needed for data taxonomy?

Data taxonomy professionals need strong analytical skills to categorize and organize data effectively, along with knowledge of data management principles and metadata standards. Familiarity with data modeling tools, taxonomy development, and understanding of business context are also important. Proficiency in tools like Excel, SQL, or specialized taxonomy software can enhance performance.

Full-time

Posted 2 days ago

New


Job description

Product Data Specialist

About McNaughton McKay Group:

McNaughton McKay Group (MMG) is a 100% employee-owned distributor of electrical and PVF (pipes, valves, and fittings) solutions, serving the industrial, commercial and construction markets. Our portfolio of trusted brands operates from more than 60 branches across nine states and Germany. At MMG, we do more than deliver products. We build lasting partnerships—backed by deep inventory and local expertise—to keep your projects moving and businesses growing. Our empowered team provides the support, insight and scalable solutions needed to navigate today’s demands and solve our customers’ most complex challenges.

Role Purpose:

This position supports the architecture and day-to-day orchestration of the company’s Product Information Management (PIM) platform (Stibo STEP) and related data pipelines. The role serves as an operational partner to the Product Data Manager, helping monitor automated workflows and suggesting and implementing improvements to optimize them for efficiency, maintaining documentation and version control, triaging incoming data quality issues, and supporting the rollout of new platform initiatives. The position requires familiarity with data workflows, automation tooling (particularly Alteryx), and the operational systems the PIM platform connects to, including the ERP and ecommerce channel.

As a Product Data Specialist, you will:

  • Monitor automated PIM and Alteryx workflow outputs; identify and escalate anomalies, failures, or data quality exceptions requiring expert resolution.
  • Maintain documentation and version control for the Alteryx and Stibo STEP automation library, including workflow change logs, process guides, and runbooks.
  • Support rollout of new platform initiatives, including testing, validation, and coordination with the external integrator under direction of the Product Data Manager.
  • Perform first-level triage on service desk tickets related to PIM data, ecommerce product content, and ERP product attributes; resolve or escalate appropriately.
  • Execute defined data quality improvement tasks: reviewing enrichment output, identifying classification gaps, and flagging records for remediation.
  • Assist with taxonomy maintenance, attribute schema updates, and category-level data standards as directed.
  • Contribute to the enrichment and publishing pipeline for standard catalog products, supporting match rate improvements against IDEA and Affiliated Distributors aggregator feeds.
  • Support onboarding of new product data into the PIM platform, including data mapping, validation, and workflow testing.
  • Collaborate with the Product Data Manager and cross-functional stakeholders to document data standards and support process improvement efforts.
  • Perform application testing during Stibo STEP upgrades and ongoing development initiatives.

Desired Knowledge/Skills/Abilities Include:

  • Bachelor’s degree in a related field plus 3–5 years of professional experience in data operations, data analytics, or a related discipline. Equivalent experience considered in lieu of degree.
  • Proficiency in Alteryx Designer for building, running, and maintaining data workflows. Hands-on experience with workflow scheduling, data blending, and output validation.
  • Experience in a PIM or MDM platform in a professional setting — managing product data, taxonomy, enrichment workflows, or data governance. Experience with Stibo STEP specifically is a strong plus.
  • Solid understanding of relational database concepts and SQL — comfortable reading, writing, and troubleshooting queries involving joins, filtering, aggregation, and subqueries. Ability to use SQL to investigate data issues and validate pipeline outputs independently.
  • Understanding of programming and scripting concepts, particularly Java and JavaScript, is a plus. Familiarity with these languages supports platform configuration, workflow scripting, and integration troubleshooting within enterprise data environments like Stibo STEP.
  • Understanding of how master data (product, customer, supplier) relates to sales, purchasing, ecommerce, and operational reporting.
  • Demonstrated interest in adopting new technologies and AI-powered tools to improve how work gets done — whether independently or collaboratively. Candidates who actively use or are curious about emerging tools for data work, problem-solving, and workflow automation are strongly preferred.
  • Proficiency in Microsoft Excel or equivalent tools for data review and validation; familiarity with AI-assisted alternatives is a plus.
  • Strong attention to detail; ability to identify data anomalies and inconsistencies within large datasets.
  • Strong organizational skills with a consistent habit of maintaining clean, up-to-date documentation — process guides, workflow logs, change records, and runbooks.
  • Ability to work independently on defined tasks, manage competing priorities, and communicate proactively when blockers arise.
  • Experience with XML and FTP file transfers preferred. Working knowledge of Linux operating systems a plus, particularly in relation to server-side data operations and digital asset workflows.

Reporting Structure:

Reports To: Product Data Manager

Direct Reports: None

Working Conditions:

Normal office environment; occasional after-hours work may be required during platform updates or initiative rollouts.

EEO/AA/M/F/Vet/Disability Employer:

The above statements are intended to describe the essential functions and related requirements of persons assigned to this job.  They are not intended as an exhaustive list of all job duties, responsibilities and requirements.