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Data Taxonomy Jobs (NOW HIRING)

Exactech

$57.75 - $74.25/hr

This specific role focuses on data decomposition, building conceptual models, developing an enterprise clinical data taxonomy, and developing a logical clinical data model at the enterprise level.

Covetrus

Taxonomy Analyst

Chicago, IL · On-site

Build and understand taxonomy development and consumption through various data pipelines ... Perform data mapping using various product and patient demographic taxonomies. Partner with ...

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Data Taxonomy information

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 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 the process of classifying and organizing data into hierarchical categories or groups based on shared characteristics or attributes. This structure helps organizations manage, retrieve, and analyze data more efficiently by making it easier to find and use relevant information. Data taxonomy is essential for data governance, improving search and discovery, and supporting compliance with data policies. It is commonly used in various industries to ensure consistency and clarity in data handling and reporting.

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.

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Data Taxonomy jobs near you
Infographic showing various Data Taxonomy job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, and 99% Full Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
SAP FI Analyst Level IV - Data Design Lead

SAP FI Analyst Level IV - Data Design Lead

First Genesis

Houston, TX • On-site

Contractor

Posted 21 days ago

Job description

Job Description

Work Location: The Woodlands, TX

Job Title: IT - Application - SAP FI Analyst Level IV


Job Description: Expert level Central Finance, SAP Finance, HANA developer

Need: Our client has an immediate opening for a Data Design Lead in its Data and Analytics team. The team works closely with the business to proactively develop solutions, deliver training, and understand the current and future technologies needed to understand data.

Work environment: The work environment is fast paced and dynamic. Individuals will be handling multiple activities in a team as well as individual contributor environment.

Primary functions: data architecture, data analysis and design, data standardization, data quality management, reference and master data management, data integration, data governance

Primary Deliverables: Data architecture, data flow, logical models, physical source data models, data profiling reports and data audits, data definitions, data taxonomy, data insights, meta-data, data lineage, data cleansing services

Activities: data modeling, data audit, detailed data design, define rules, establish master data solutions, define hierarchies and affiliations, profile|analyze|assess data quality, design data quality management procedures, clean and correct data quality defects, establish data governance

Requirements:

Demonstrate critical thinking, analytical skills, and employ judgment to offer thoughtful, concise input toward resolutions of problems.

Be able to translate data requirements into business processes and reverse engineer business processes into data requirements

Comprehension of DevOps and Agile development and application to data centric architecture and solutions

Strong communication and interpersonal skills with strong English proficiency

Leadership skills needed to successfully promote ideas, coordinate work activities, and plan deliverables within a project team.

Minimum Bachelor's Degree in Engineering Technology, Computer Science, or closely related field.

Be able to easily communicate both to the Business as well as to the technical

Be able to set expectations and to follow deadlines

Technical Competencies:

Advanced expert database handling languages

Expert in data modeling (physical and logical), ER diagrams, data dictionary, normalize/denormalize, agile data modeling

Expert in data manipulation tools such as: SSMS, SSIS, TOAD, Access, Excel, Info Steward, Data Services, SAP SDI / SDA

Practical skill sets in BI and Data visualization tools is desirable

Some knowledge of other programming languages and ability to write code (e.g.: .NET, Angular, python, XML) is desirable

Working knowledge of ETL

Working knowledge of SAP

Working experience in integrating SAP to non-SAP systems together

Basic Project Management and Business Process modeling

A minimum of 5 years' experience in the SAP FiCo module, including understanding in Data Management and Governance

Advanced competency in the T-SQL language

Experienced in handling/integrating large volumes of data

Preferably (or Desirable) a Good to Expert level of knowledge in:

SAP Central Finance

SAP HANA Modeling and/or HANA EIM

SAP Data Services (Data Extract, Data Profiling, de-duplication)

Main SAP FiCo tables

Tableau

Additional Information

All your information will be kept confidential according to EEO guidelines. #3964

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