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Data Taxonomy Jobs in Oregon (NOW HIRING)

e.l.f. Beauty

OR · Hybrid

$153K/yr

Customer Data Strategy: Define and maintain the company's customer data strategy, including data taxonomy, schema ownership, event instrumentation standards, consent management, and cross-platform ...

e.l.f. Beauty

OR · Hybrid

$80K - $130K/yr

Customer Data Strategy: Define and maintain the company's customer data strategy, including data taxonomy, schema ownership, event instrumentation standards, consent management, and cross-platform ...

NewRocket

AI Data Intelligence Lead

OR · Remote

Automated classification and taxonomy generation * Anomaly detection and data quality monitoring * Achema mapping and data harmonization across datasets * AI Data Architecture * Design modern data ...

Degreed

OR

NET and ESCO, and you understand how AI-based skill matching depends on taxonomy quality. * Data product mindset. You have managed structured data with clear ownership, versioning, quality standards ...

Rush Street Interactive

Instrumentation Analyst

OR · Remote

By ensuring event data is accurately defined and consistently implemented, this role enables ... Enforce governance standards related to taxonomy, required fields, naming conventions, and event ...

Skillsoft

Sr. Federal Customer Success Manager

OR · Remote

$118K - $131K/yr

Guide customers through taxonomy decisions, benchmarks, and readiness planning * Articulate the value to the customer of each of these approaches Data-Led Insights and Decision Making * Use data to ...

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All JobsData Taxonomy JobsData Taxonomy Jobs in Oregon

Data Taxonomy information

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Lead Data Scientist, Data Science Director, or Chief Data Officer, which typically require extensive experience, advanced skills in machine learning and big data tools, and often involve strategic decision-making responsibilities. These roles can command salaries exceeding $150,000 annually, depending on the industry and location.

How to get a job in taxonomy?

To get a job in taxonomy, develop expertise in data organization, classification, and metadata standards such as Dublin Core or schema.org. Gaining skills in data management tools, understanding industry-specific vocabularies, and obtaining relevant certifications can improve employability. Experience with data analysis and information architecture is also valuable for roles in taxonomy development and management.

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 is data taxonomy?

Data taxonomy is a structured classification system that organizes data into categories and subcategories, making it easier to manage, search, and analyze. Data professionals often use standards and tools like metadata and ontologies to develop effective taxonomies for data governance and integration.

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.

What do you need to be a data taxonomy specialist?

A data taxonomy specialist typically needs a strong understanding of data management, classification, and metadata standards, along with skills in data modeling and taxonomy development. Proficiency in tools like Excel, SQL, or specialized taxonomy software is often required, and relevant certifications in data management or information architecture can be beneficial. Experience with data governance and collaboration with cross-functional teams also supports success in this role.

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 are popular job titles related to Data Taxonomy jobs in Oregon? For Data Taxonomy jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Data Taxonomy jobs in Oregon look for? The top searched job categories for Data Taxonomy jobs in Oregon are:
What cities in Oregon are hiring for Data Taxonomy jobs? Cities in Oregon with the most Data Taxonomy job openings:
Data Taxonomy jobs near you
Infographic showing various Data Taxonomy job openings in Oregon as of July 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Digital ID Data Analyst

BizTek People, Inc. | APA International Placement Consultants

Beaverton, OR • On-site

Contractor

Posted 12 days ago

Job description


Key Responsibilities
• Build & own insights & metrics requirements' backlog across functions
• Work with business to gather insights / metrics requirements, define business logic & analyze the
data needed to build them
• Query datasets from various data sources and perform ad-hoc data analysis
• Establish partnerships with cross-functional enablers including data quality, data ingestion, and
business team members
• Perform data analysis across domains like line plan, sales orders, channels etc. to support
'Tagging Coverage' reporting
• Support buildout of 'Ongoing Monitoring' metrics to accelerate stabilization of OB scanning
capability
• Perform detailed analysis & accelerate developing of critical scanning metrics like Scan Accuracy
& GTIN / Inv accuracy
• As the Digital ID 'data' subject matter expert, partner with capability and analytics teams to
drive adoption of 'item level' data
• Support formulation of problem statement and definition of scope
• Analyze and understand root cause(s) to inform solution options
• Map business process flows (As-Is and To-Be)
• Gather feature requirements and use cases
• Inform roadmap and guide testing/validation
• Support identification of risks and mitigation approaches
• Engage with key stakeholders and super users to gather requirements and pilot/scale solutions
• Work functionally - Supply Chain, Procurement, Global Manufacturing, etc - both
with business and analytic teams
Requirements
Qualifications
• Bachelor's Degree in computer science, MIS, analytics, other quantitative disciplines, or related
fields
• 5+ years of relevant experiences in data & analytics product creation and adoption
• Strong hands on experience with SQL, Python, AWS, Snowflake, Databricks, Tableau & related
toolsets
• A strong history of supporting cross functional data product delivery teams
• Excellent communications skills (written and verbal) and strong interpersonal skills
• Understanding of data architecture, data taxonomy, and both structured and unstructured data
• Experience with agile development methodologies
• Experience with real-time data collection and processing
Skill Set
data

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