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Data Taxonomy Jobs in Utah (NOW HIRING)

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Develop and maintain IT cost taxonomy aligned to TBM standards (IT Tower, Cost Pool, and Service ... Refine and validate ROM calculations using actual cost data, vendor quotes, and benchmarking ...

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Develop and maintain IT cost taxonomy aligned to TBM standards (IT Tower, Cost Pool, and Service ... Refine and validate ROM calculations using actual cost data, vendor quotes, and benchmarking ...

Define legal taxonomy and structure. Bring frameworks like practice-area ontologies, document ... data, or similar disciplines. * Genuine fluency with modern AI development. You build with tools ...

Translate data into briefing improvements. * Cross-Team Collaboration: Serve as the primary UGC ... Content library rebuilt or reorganized with clean taxonomy -- paid and organic teams pulling from ...

Maintain call-driver taxonomy and QA standards that hold up across a diverse brand set, so cross-brand comparisons stay meaningful * Identify and escalate data-capture gaps that limit diagnosis for ...

Architect and own the full capture, transcription, structuring, and edge-case taxonomy pipeline for ... Evaluate and integrate speech-to-text, large language model (LLM), and data-structuring tooling ...

Architect and own the full capture, transcription, structuring, and edge-case taxonomy pipeline for ... Evaluate and integrate speech-to-text, large language model (LLM), and data-structuring tooling ...

Maintain call-driver taxonomy and QA standards that hold up across a diverse brand set, so cross-brand comparisons stay meaningful * Identify and escalate data-capture gaps that limit diagnosis for ...

... site taxonomy and facets * Use AI tools (ChatGPT, Claude, Copilot, or similar) to analyze ... Strong analytical skills; comfortable interpreting sales and inventory data * Clear written and ...

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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 Utah? For Data Taxonomy jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Data Taxonomy jobs? Cities in Utah with the most Data Taxonomy job openings:
Infographic showing various Data Taxonomy job openings in Utah 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.
Senior Software Engineer- Big Data & MCP, Data Foundations

Senior Software Engineer- Big Data & MCP, Data Foundations

RevSpring

Salt Lake City, UT โ€ข On-site

$110K - $133K/yr

Full-time

Posted 28 days ago


Job description

Job Summary:
RevSpring is a company focused on providing innovative data solutions, and they are seeking a Senior Software Engineer specializing in Big Data and data foundations. The role involves designing and optimizing data pipelines, developing backend services, and ensuring data performance and quality in a healthcare context.
Responsibilities:
โ€ข 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.
โ€ข 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.
โ€ข 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.
โ€ข Optimize Data & Search Performance: Deeply tune pipeline throughput, data warehouse performance, and search indexing โ€” optimizing BigQuery cost and query performance and Elasticsearch index design to ensure data freshness, relevance, and scalability across high-volume datasets.
โ€ข 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.
โ€ข 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.
Qualifications:
Required:
โ€ข 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.
โ€ข 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).
โ€ข Working experience with search indexing and Elasticsearch, including index management, mappings, and building and maintaining search indices from pipeline output.
โ€ข 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.
โ€ข 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.
โ€ข Familiarity with healthcare data standards (e.g., NPPES/NPI registries, NUCC Provider Taxonomy, machine-readable files (MRFs) for cost transparency, and FHIR).
โ€ข Experience with data quality and pipeline testing frameworks (e.g., dbt tests, Great Expectations) and streaming/event ingestion (e.g., Pub/Sub, Kafka).
โ€ข Experience integrating graph-based data and healthcare taxonomy ontologies to enrich datasets and search query context.
โ€ข Experience with observability and logging platforms (e.g., DataDog) for monitoring pipeline health and data freshness.
โ€ข Bachelorโ€™s Degree
โ€ข 5+ years of professional experience with Python, with strong software-engineering fundamentals (testing, code review, design).
โ€ข 3+ years experience with Java or another JVM language is also high desired, particularly for Beam/Dataflow.
โ€ข Ability to read, analyze and interpret general business periodicals, professional journals, technical procedures or governmental regulations.
โ€ข Ability to write reports, business correspondence and procedure manuals.
โ€ข Ability to effectively present information and respond to questions from a variety of both internal and external sources.
Preferred:
โ€ข BigQuery experience is a plus.
โ€ข Familiarity with hybrid (BM25 + semantic/vector) search is a plus.
โ€ข 3+ years of GCP experience preferred.
Company:
RevSpring is a provider of revenue cycle technology services offering data analytics, multi-channel customer communications. Founded in 1997, the company is headquartered in Wixom, USA, with a team of 501-1000 employees. The company is currently Late Stage.