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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 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 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 Virginia? For Data Taxonomy jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Data Taxonomy jobs in Virginia look for? The top searched job categories for Data Taxonomy jobs in Virginia are:
What cities in Virginia are hiring for Data Taxonomy jobs? Cities in Virginia with the most Data Taxonomy job openings:
Data Taxonomy jobs near you
Infographic showing various Data Taxonomy job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

AWS Data Automation Engineer

Node.Digital

Arlington, VA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago

Job description

AWS Data Automation Engineer 

Location: Arlington, VA

Must have an active Top Secret Security Clearance

Node is supporting a U.S. Government customer to provide support for onsite incident response to civilian Government agencies and critical asset owners who experience cyber-attacks, providing immediate investigation and resolution.  Contract personnel perform investigations to characterize the severity of breaches, develop mitigation plans, and assist with the restoration of services. 

Node is seeking an AWS Data Automation Engineer to support this critical customer mission.

The Data Automation Engineer will develop and implement automation solutions to support technology integration activities, focusing on data pipeline development, automated analysis workflows, and integration automation. This role addresses manual workflow pain points and enables scaling of technology capabilities through intelligent automation.

Responsibilities:

- Develop automated data pipelines for technology integration initiatives

- Create automation workflows for malware sample collection, detonation, and taxonomy

- Implement data integration automation between pilot and production systems

- Support Automated Malware Analysis (AMA) platform development and enhancement

- Develop scripts and tools to automate repetitive technical tasks

- Create data transformation and normalization automation

- Support AI/ML data preparation and feature engineering automation

- Develop monitoring and alerting automation for integrated systems

- Implement API integrations for data sharing and workflow automation

- Document automation solutions and maintain code repositories

- Support scaling automation from pilot to production environments

- Optimize automation performance and efficiency

- Collaborate with analysts to identify automation opportunities

- Ensure automation solutions maintain data quality and integrity

- Support continuous improvement of automated capabilities

Requirements

Required Skills:
- U.S. Citizenship
- Active Secret clearance; TS/SCI preferred
- Ability to obtain Department of Homeland Security (DHS) Entry on Duty (EOD) Suitability
- 5+ years of experience in automation engineering, data engineering, or software development
- Subject matter expertise of core AWS components including VPCs, EC2, EKS, IAM, SQS, SNS, Lambda, and Route 53
- Experience with data ingestion pipeline design on AWS
- Experience with S3 data storage architecture and schema design for analytic workflows
- Strong programming skills in Python, with experience in data manipulation libraries
- Experience developing data pipelines and ETL processes
- Knowledge of automation frameworks and orchestration tools
- Experience with APIs and integration technologies
- Understanding of database systems and data modeling
- Familiarity with version control (Git) and CI/CD practices
- Strong problem-solving and analytical skills
- Ability to translate business requirements into automated solutions
- Strong analytical and problem-solving skills
- Excellent documentation and communication abilities
Desired Skills:
- Experience with malware analysis automation or cybersecurity tools
- Experience with AWS support service configurations (AWS Budget, EMR, Kinesis, GuardDuty, Cloudwatch, OpsWorks)
- Knowledge of AI/ML pipelines and data preparation
- Experience with workflow orchestration tools (Airflow, Prefect)
- Background in cybersecurity or threat intelligence automation
- Experience with containerization and orchestration (Docker, Kubernetes)
- Knowledge of streaming data platforms (Kafka, Kinesis)
- Familiarity with big data technologies (Spark, Hadoop)
- Experience supporting federal cybersecurity programs
Required Education:
BS in Computer Science, Data Science, or related degree, or HS Diploma and 7+ years of directly relevant experience
Desired Certifications:
- DoD 8140 IAT Level III
- CSSLP

Benefits

We are proud to offer competitive compensation and benefits packages to include

  • Medical 
  • Dental
  • Vision
  • Basic Life 
  • Health Saving Account
  • 401K matching
  • Three weeks of PTO/Sick
  • 11 Paid Holidays
  • Pre-Approved Online Training

Apply