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Data Taxonomy Jobs in Portland, OR (NOW HIRING)

KEEN Footwear

Sr. Web Merchandiser

Portland, OR

$95K - $101K/yr

Manage attributes, taxonomy, trending keywords, and navigation structure and make recommendations ... Experience with ecommerce product data, discovery and merchandising software. * Working knowledge ...

KEEN Footwear

Sr. Web Merchandiser

Portland, OR · On-site

$95K - $101K/yr

Manage attributes, taxonomy, trending keywords, and navigation structure and make recommendations ... Experience with ecommerce product data, discovery and merchandising software. * Working knowledge ...

All JobsData Taxonomy JobsData Taxonomy Jobs in Portland, OR

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.

What are popular job titles related to Data Taxonomy jobs in Portland, OR?

For Data Taxonomy jobs in Portland, OR, the most frequently searched job titles are:

What job categories do people searching Data Taxonomy jobs in Portland, OR look for?

The top searched job categories for Data Taxonomy jobs in Portland, OR are:

Data Taxonomy jobs near you
Infographic showing various Data Taxonomy job openings in Portland, OR as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Senior Software Engineer- Big Data & MCP, Data Foundations

RevSpring, Inc.

Portland, OR • On-site

$121K - $145K/yr

Full-time

Re-posted 28 days ago

Job description

Job Title: Senior Software Engineer- Big Data & MCP, Data Foundations
Job Summary:
Essential Functions:
  • Collaborate and Innovate: Partner with product managers, data engineers, and business leaders to translate complex product and data requirements into scalable, reliable data pipelines and the search experiences they power.
  • Architect Data Pipelines: Design, build, and optimize large-scale distributed batch and streaming pipelines (using Apache Airflow, Apache Beam/Dataflow, and DBTon BigQuery) to ingest, model, and transform high-volume healthcare data into clean, well-tested, query-ready datasets and search indices.
  • Build Data Models & Backend Services: Develop resilient Python services and DBT models that power data delivery and self-service analytics, including Model Context Protocol (MCP) servers that expose curated data and tooling to downstream and AI consumers, and integrate with external REST/SOAP APIs and third-party data sources.
  • Optimize Data & Search Performance: Deeply tune pipeline throughput, data warehouse performance, and search indexing - optimizing BigQuery cost and query performance and Elasticsearch index design to ensure data freshness, relevance, and scalability across high-volume datasets.
  • Drive Engineering Excellence: Write clean, maintainable, well-tested code and lead by example through rigorous code reviews, architectural and data-modeling design discussions, and mentoring, driving a culture of high-quality software and trustworthy data.
  • Pioneer New Technologies: Stay at the forefront of modern data engineering, the analytics-engineering ecosystem (e.g., DBT, BigQuery), and information retrieval, proactively applying these advancements to strengthen our data platform and the products it powers.

Minimum Requirements:
Specific Job Skills:
  • Data Engineering: Proven experience designing and orchestrating large-scale ETL/ELT pipelines using Apache Beam/Google Cloud Dataflow (or similar), and DBT, built on modern cloud data warehouses. BigQuery experience is a plus.
  • Databases & SQL: 4+ years of experience working with relational databases and analytical data warehouses, with deep, advanced SQL skills and solid data-modeling fundamentals (e.g., dimensional and normalized modeling).
  • Search & Indexing: Working experience with search indexing and Elasticsearch, including index management, mappings, and building and maintaining search indices from pipeline output. Familiarity with hybrid (BM25 + semantic/vector) search is a plus.
  • Backend & Data Services: Experience building scalable Python services and high-performance data APIs, including developing Model Context Protocol (MCP) servers that expose data and tooling to downstream and AI consumers.
  • Infrastructure & DevOps: Strong understanding of containerization (Docker), CI/CD methodologies (e.g., GitHub Actions), Git, Infrastructure as Code (e.g., Terraform/Pulumi), and managing services within cloud platforms (3+ years of GCP experience preferred).
  • Familiarity with healthcare data standards (e.g., NPPES/NPI registries, NUCC Provider Taxonomy, machine-readable files (MRFs) for cost transparency, and FHIR).
  • Experience with data quality and pipeline testing frameworks (e.g., dbt tests, Great Expectations) and streaming/event ingestion (e.g., Pub/Sub, Kafka).
  • Experience integrating graph-based data and healthcare taxonomy ontologies to enrich datasets and search query context.
  • Experience with observability and logging platforms (e.g., DataDog) for monitoring pipeline health and data freshness.

Education: Bachelor's Degree
Experience: 5+ years of professional experience with Python, with strong software-engineering fundamentals (testing, code review, design). 3+ years experience with Java or another JVM language is also high desired, particularly for Beam/Dataflow.
Supervision: N/A
Certifications: N/A
Language Skills:
Ability to read, analyze and interpret general business periodicals, professional journals, technical procedures or governmental regulations. Ability to write reports, business correspondence and procedure manuals. Ability to effectively present information and respond to questions from a variety of both internal and external sources.
Physical Capabilities: Standard categories
The physical capabilities described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
While performing the duties of this job, the employee is regularly required to sit; use hands to finger, handle, or feel; reach with hands and arms; and talk or hear. The employee is occasionally required to stand and walk. The employee must occasionally lift and/or move up to 10 pounds. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus.
RevSpring is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Note: This Job Description may not describe all of the job responsibilities and standards assigned to this position. The duties may change from time to time. RevSpring does not discriminate against any group in hiring or employment practices. Nothing in this job description constitutes a contract for employment.

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