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Part Time Data Analyst Jobs in Virginia (NOW HIRING)

AI DevOps Analyst

Mclean, VA · On-site +1

$77K - $176K/yr

Support secure access to AI tools, safe data handling, sign-in, permissions, and logging. * Assist ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Scientist

Reston, VA · On-site

$77K - $176K/yr

On our team, you'll use your analytical skills to help create real-world impact. You'll work ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Scientist

Alexandria, VA · On-site +1

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Scientist

Chantilly, VA · On-site +1

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Scientist

Arlington, VA · On-site +1

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Scientist

Arlington, VA · On-site

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Scientist

Arlington, VA · On-site +1

$99K - $225K/yr

You'll work closely with the Marine Corps Directorate of Analysis and Performance Optimization to ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Showing results 21-40

Part Time Data Analyst information

See Virginia salary details

$33.7K

$81.9K

$134.8K

How much do part time data analyst jobs pay per year?

As of Sep 4, 2026, the average yearly pay for part time data analyst in Virginia is $81,931.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,000.00 and $96,200.00 per year, depending on experience, location, and employer.

What is a part time data analyst?

Part time data analysts are professionals who work fewer hours than a standard full-time schedule, typically analyzing and interpreting data to help organizations make informed decisions. They use statistical tools and software to process data, identify trends, and generate reports. Part time positions are ideal for those seeking flexible work arrangements, such as students, parents, or individuals with other commitments. Despite working fewer hours, part time data analysts are expected to have strong analytical skills and proficiency in data management tools. Their contributions are valuable to businesses seeking data-driven insights without the need for a full-time role.

What does a part time data analyst do?

A part-time data analyst collects, organizes, assesses, and reviews information. In this career, you review data to ensure that it is accurate and to identify trends, provide analysis of a market or a company’s operations and processes, or meet other needs of a company or client. Data analysts typically create reports that explain their analysis. Your responsibilities also include helping to develop and deploy systems and tools to collect, extract, and categorize data so that you can analyze it more efficiently. As a part-time employee, you perform your duties for less than 40 hours per week.

What are the key skills and qualifications needed to thrive as a part time data analyst, and why are they important?

To excel as a Part Time Data Analyst, you need proficiency in data analysis, statistical methods, and a relevant degree such as mathematics, statistics, or computer science. Familiarity with technical tools like Microsoft Excel, SQL, and data visualization platforms such as Tableau or Power BI is typically required. Attention to detail, problem-solving ability, and effective communication are crucial soft skills for interpreting and presenting data insights. These competencies enable accurate, actionable analyses that support decision-making, even within limited working hours.

How does a part time data analyst typically collaborate with full time team members to ensure project continuity?

As a part-time data analyst, you’ll often work closely with full-time analysts, project managers, and business stakeholders to maintain seamless project progress. Regular check-ins, clear documentation of your analyses, and using collaborative tools like shared dashboards or project management software are key practices. Flexibility and strong communication skills are essential, as you may need to align your schedule with team meetings or coordinate handoffs to ensure your work integrates smoothly with ongoing projects.

What is the difference between Part Time Data Analyst vs Data Scientist?

AspectPart Time Data AnalystData Scientist
Required CredentialsBachelor's degree in data-related field; some roles may require certifications like Microsoft Excel or SQLBachelor's or master's degree in data science, statistics, or related fields; often requires programming skills and certifications
Work EnvironmentTypically in office settings, supporting specific projects or departments, with flexible or part-time hoursUsually in tech or research environments, working on complex models and large datasets, often full-time
Employer & Industry UsageUsed across industries like finance, marketing, healthcare for data reporting and analysisCommon in tech, finance, and research sectors for developing predictive models and advanced analytics

While both roles involve data analysis, Part Time Data Analysts focus on supporting business decisions with basic data tasks, often on a flexible schedule. Data Scientists handle complex modeling and predictive analytics, typically in full-time roles. The choice depends on your skills, experience, and career goals.

Are part time data analyst jobs still in demand?

Part-time data analyst jobs remain in demand as organizations seek flexible ways to analyze data for decision-making. Skills in Excel, SQL, and data visualization tools like Tableau are valuable, and remote or flexible schedules are increasingly available in this field.

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

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

What cities in Virginia are hiring for Part Time Data Analyst jobs?

Cities in Virginia with the most Part Time Data Analyst job openings:

Infographic showing various Part Time Data Analyst job openings in Virginia as of August 2026, with employment types broken down into 100% Part Time. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $81,931 per year, or $39.4 per hour.

Fellow, Data Engineering

Systems Planning and Analysis

Alexandria, VA • On-site

$115K - $139K/yr

Full-time, Part-time

Medical, Life, Retirement

Re-posted 10 days ago


Job description

Overview

Systems Planning and Analysis, Inc. (SPA) delivers high-impact technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, we are known for continuous innovation for our government customers, both in the US and abroad. Our exceptionally talented team is highly collaborative in spirit and practice, producing Results that Matter. Come work with the best! We offer opportunities, unique challenges, and clear-sighted commitment to the mission. SPA: Objective. Responsive. Trusted. 

SPA has established a Fellows program in which there are positions aligned to Capabilities and Domains in support of the entire SPA company across all Divisions.  The Data Engineering Fellow serves as the corporate lead responsible for providing strategic leadership, guidance, and experienced mentoring across SPA in technology and innovation related to Data-driven Engineering, Analytics, and Architectures in support of present and future systems. SPA remains a forefront leader in delivering cutting-edge analytics, modeling & simulation solutions, wargaming, and resilient accurate integrated engineering solutions to clients across the Federal Government.  At the core of all this capability is the underlying data architecture, tools, and capabilities. 

Responsibilities

The Data Engineering Fellow reports into the Chief Capabilities Office (CCO) and will help SPA design and mature robust data architectures and analytic approaches that leverage a wide range of data types (e.g., structured/tabular, log data, text, imagery, video, sensor/telemetry) to deliver actionable insights for government customers. The focus is on turning structured and unstructured, distributed data into reliable, secure, and usable information to support the customer mission.

This is a fractional, part-time role expected to average approximately 40 hours per quarter (roughly one week of full-time effort every three months), focused on high-impact strategic contributions rather than day-to-day operations.  Contributions will advance the Capability expertise broadly across the many Domains SPA supports.

The responsibilities are defined as follows:

Cultivation of market-relevant SPA expertise in data engineering and analytics:

  • Define expert knowledge and skills across Beginner, Intermediate, and Advanced levels, focusing on current market needs and future anticipation through inciteful industry knowledge and engagement. Sustain structured repositories including white papers, case studies, and pedigreed data sets to facilitate expertise development and collaboration. Implement quality assurance within training, products, and development processes related to data engineering. Define an expertise assessment process leading to tiered certifications for the Capability. Create objective, appropriate, and transparent assessment methods to certify expertise levels for Data Engineers, Data Analyst, and Data Architects at SPA. Leverage external certifications and qualifications for assisting SPA in playing and executing credible training in areas of Data Engineering and Analytics.
  • Ensure the conduct of high-quality training at all expert levels. Promote best practices, emerging techniques, and professional development. Provide high-quality training across data engineering disciplines through community of practice, training, and various levels of engagement.  Work across SPA to assure accessible training and information for data engineers across SPA.. Encourage personal expertise growth, focusing on mentoring young, mid-level and more experienced personnel.

Market & Client Visibility:

  • Ensure SPA expertise representation is evident across market/client platforms, conferences, and social media as beneficial to the business.
  • Participate in strategy sessions for data-driven solutions on high-priority opportunities. Support proposal development by contributing insights or identifying expertise partners.
  • Train the team in client engagement, professional presentations, and writing-highlighting responsible handling of classified information. Support customer meetings and engagements as appropriate to assisting the capture and BD process.

Be at the cutting edge:

  • Lead forward-looking initiatives that support innovation & influence, stay ahead of market trends and prevent client surprises while contextualizing innovation historically. Advocate for new areas of expertise to fulfill client needs and position SPA as an industry thought leader, with particular emphasis on the following areas
    • Strategic data and analytics guidance: Provide periodic strategic guidance on SPA's enterprise data engineering and analytics strategy, ensuring alignment with government customer mission requirements and federal priorities such as national security, mission efficiency, and responsible data use.
    • Architecture and technical review: Review and advise on the design of data platforms and pipelines (e.g., data lakes, warehouses, streaming architecture) that ingest, transform, and curate diverse data types at varying scales and security levels. Participate in targeted design reviews and technical deep dives rather than continuous implementation.
    • Data governance and best practices: Advise on data modeling, data quality, data storage, data lakes, data access controls, and data governance frameworks, including alignment with federal data policies. Help define reference architectures, standards, and patterns; validate that proposed solutions are accurate, reproducible, and mission aligned.
    • Advanced data engineering, analytics, and predictive modeling:  Provide expert input on the curation, ingest, normalization, and labeling of data for statistical models, forecasting approaches, anomaly detection methods, and machine learning solutions for mission problems (e.g., force readiness, intelligence analysis, logistics optimization, operational risk). Focus on mission-specific data sources, formats, and platform integration requirements.
    • Visualization and decision support: Advise on the design principles and overall approach for dashboards, geospatial products, and interactive visualizations that support senior decision-makers. Review and critique key artifacts rather than building them directly.

Data Engineering Support for Artificial Intelligence: Advance SPA's capability development by assisting the Applied AI Fellow in incorporating data engineering best practices into emerging Artificial Intelligence (AI) methods and architectures. Guide the curation, ingest, formatting, and labeling of data to support AI enablement, including machine learning and automation approaches to strengthen analytic rigor, improve model performance, and enhance enterprisewide decisionsupport solutions.

Qualifications

Required Qualifications:

  • Active DoD Secret clearance with ability to obtain and maintain a Top Secret clearance
  • Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Engineering, Mathematics, or a related technical discipline
  • 15+ years of progressively responsible experience in data engineering, enterprise data architecture, analytics, or related technical leadership roles
  • Demonstrated national-level technical leadership and recognition as a subject matter expert in data engineering, enterprise data architecture, or advanced analytics, evidenced by significant technical contributions, publications, invited speaking engagements, leadership of major government initiatives, patents, or comparable accomplishments
  • Demonstrated expertise designing, evaluating, and advising on enterprise-scale data architectures supporting structured, semi-structured, and unstructured data across complex mission environments
  • Extensive experience with data platforms, data lakes, data warehouses, ETL/ELT pipelines, streaming architectures, cloud-native data ecosystems, and modern data integration practices
  • Experience supporting U.S. Government, Department of Defense, Intelligence Community, or other federal customers
  • Deep understanding of data governance, metadata management, data quality, master data management, data security, and federal data standards and policies
  • Demonstrated experience enabling advanced analytics, artificial intelligence, machine learning, and predictive analytics through scalable data engineering practices
  • Proven ability to provide strategic technical guidance to executive leadership, chief engineers, program managers, and multi-disciplinary engineering teams
  • Demonstrated experience mentoring technical professionals, developing communities of practice, and building organizational capability through training and knowledge sharing
  • Excellent written and verbal communication skills, including experience authoring technical white papers, strategy documents, executive briefings, and proposal content

Desired Qualifications

  • Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Engineering, Applied Mathematics, or a related technical discipline
  • Active Top Secret/SCI security clearance
  • Experience architecting secure cloud-based data solutions within AWS, Microsoft Azure, Google Cloud, GovCloud, or classified cloud environments
  • Expertise with modern data engineering platforms and technologies such as Databricks, Snowflake, Apache Spark, Kafka, Airflow, dbt, Delta Lake, or comparable technologies
  • Experience supporting national security missions involving defense, intelligence, cyber, space, homeland security, or related domains
  • Familiarity with the DoD Digital Engineering Strategy, DoD Data Strategy, CJADC2, Digital Twins, Model-Based Systems Engineering (MBSE), or related digital transformation initiatives
  • Experience establishing enterprise data governance frameworks, reference architectures, technical standards, and best practices
  • Relevant professional certifications (e.g., AWS Certified Data Engineer, Microsoft Azure Data Engineer Associate, Google Professional Data Engineer, Databricks Certified Data Engineer, Snowflake SnowPro, DAMA CDMP, TOGAF)
  • Established professional relationships across government, industry, academia, and professional organizations that enhance SPA's visibility and technical leadership

At SPA, we strive to deliver a robust total compensation package that will attract and retain top talent.  Elements of the compensation package include competitive base pay and variable compensation opportunities.  SPA provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide both paid and unpaid time away from work.  The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, etc.  Please note that the salary information shown below is a general guideline only.  Salaries are commensurate with experience and qualifications, as well as market and business considerations.  Pay Transparency Range:  175k - 265k

Pay Range InformationAt SPA, we strive to deliver a robust total compensation package that will attract and retain top talent. Elements of the compensation package include competitive base pay and variable compensation opportunities. SPA provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work. The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, etc. Please note that the salary information shown below is a general guideline only. Salaries are commensurate with experience and qualifications, as well as market and business considerations. Virginia, Pay Transparency Salary range: USD $175,000.00/Yr. - USD $265,000.00/Yr.Employment Type: OTHER