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Data Organization Jobs in Virginia (NOW HIRING)

Ampcus Inc

Systems Administrator II

Reston, VA · On-site

... data organization, storage efficiency, and collaboration workflows. • Research and implement new Box features, tools, and automation capabilities to enhance productivity and security. • Ensure ...

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$10

$38

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How much do data organization jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for data organization in Virginia is $38.53, according to ZipRecruiter salary data. Most workers in this role earn between $15.43 and $60.32 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in a data organization position, and why are they important?

To thrive in a Data Organization role, you need strong analytical skills, attention to detail, and experience with data management practices, typically supported by a degree in information science, computer science, or a related field. Familiarity with database software such as SQL, data visualization tools, and proficiency in Excel or data management platforms are commonly required, while certifications like Certified Data Management Professional (CDMP) can be advantageous. Excellent organizational, problem-solving, and communication skills help facilitate effective collaboration across teams and ensure data quality. These skills are crucial for maintaining accurate, accessible, and secure data, directly impacting business decision-making and operational efficiency.

What is a data organization?

A Data Organization job involves structuring, managing, and maintaining data to ensure its accuracy, accessibility, and usability. Professionals in this role work with databases, metadata, and data governance practices to optimize information flow and retrieval. They may also clean, categorize, and integrate data from various sources to support business operations and decision-making. Strong analytical skills, attention to detail, and proficiency with data management tools are essential for success in this role.

What are some typical responsibilities I can expect in a data organization position?

In a Data Organization role, you will typically be responsible for structuring, maintaining, and ensuring the accuracy and integrity of large datasets. This often includes tasks such as data cleansing, standardizing formats, updating records, and organizing information to support business analysis or reporting needs. You may also work closely with cross-functional teams, providing data support, troubleshooting data issues, and helping to implement data governance policies. These responsibilities are essential to keep organizational data reliable and easily accessible for those who need it.

What are the most commonly searched types of Data Organization jobs in Virginia?

The most popular types of Data Organization jobs in Virginia are:

What are popular job titles related to Data Organization jobs in Virginia?

For Data Organization jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Data Organization jobs in Virginia look for?

The top searched job categories for Data Organization jobs in Virginia are:

Data Organization jobs near you
Infographic showing various Data Organization job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $80,138 per year, or $38.5 per hour.

Innovation and Automation Specialist

Accenture Federal Services

Arlington, VA • On-site

Full-time

Re-posted 28 days ago

Accenture Federal Services rating

8.7

Company rating: 8.7 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

46th of 491 rated business services

Job description

As a Data Engineer Specialist on the Innovation and Automation team, you will serve as a subject matter expert, blending deep data engineering expertise with a passion for automation. You will not build individual data pipelines for business users; instead, you will build the factory that produces them. Your mission is to design, develop, and implement the reusable frameworks, automated patterns, and core tooling that our data engineering teams will use to build their own pipelines faster, more reliably, and more consistently. This is a highly technical, hands-on role for a problem-solver who wants to act as a force multiplier for the entire data organization.

Responsibilities:

  • Act as a technical expert on the design and implementation of automated data engineering solutions
  • Develop and maintain a library of standardized, reusable ETL/ELT pipeline templates using Python, SQL, and frameworks like Databricks or Snowflake
  • Engineer and implement robust, automated data quality and testing frameworks (e.g., using tools like Great Expectations) that are embedded within the core pipeline templates
  • Contribute to the development of Infrastructure-as-Code (IaC) modules (Terraform) for the automated provisioning of data infrastructure
  • Enhance and optimize the CI/CD for Data (DataOps) pipelines, ensuring seamless and reliable deployment of data workflows
  • Serve as an escalation point for the most complex data engineering and automation challenges, providing expert-level troubleshooting and guidance to other engineers
  • Mentor other data engineers on automation best practices, code standards, and the use of the frameworks you build
  • Research and prototype cutting-edge data engineering and automation technologies to drive continuous improvement

Must have: 

  • 5+ years of hands-on experience in data engineering
  • Expert-level programming skills in Python and advanced SQL
  • Proven, in-depth experience building and optimizing data pipelines in a cloud environment (AWS, Azure) on platforms like Databricks or Snowflake
  • Strong, hands-on experience with Infrastructure-as-Code (IaC) using Terraform
  • Demonstrable experience with CI/CD principles and tools (e.g., GitLab CI, Jenkins, GitHub Actions) applied to data workflows
  • Deep understanding of modern data architecture, data modeling, and software engineering best practices

Nice to have:

  • Experience in a DevOps or Site Reliability Engineering (SRE) role
  • Direct experience developing and operationalizing a "pipeline factory" or similar framework
  • Familiarity with data orchestration tools (e.g., Airflow) and containerization (Docker, Kubernetes)
  • Experience working in a high-security DoD or Intelligence Community environment
  • Proven ability to diagnose and resolve complex performance, data quality, and system-level issues

Security Clearance:

  • Active TS or TS/SCI clearance

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