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Part Time Data Engineering Jobs in Virginia (NOW HIRING)

Data Engineer

Chantilly, VA · On-site +1

$77K - $176K/yr

Experience with data engineering projects supporting data science, AI/ML implementations, and ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Engineer, Mid

Alexandria, VA · On-site +1

$62K - $141K/yr

Bachelor's degree Nice If You Have: * 3+ years of experience building enterprise data engineering ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Engineer

Arlington, VA · On-site +1

$62K - $141K/yr

Experience with Agile engineering practices * TS/SCI clearance with a polygraph Clearance ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Engineer

Reston, VA · On-site

$77K - $176K/yr

Experience with Agile engineering practices * Bachelor's degree in a Data or IT-related field ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Engineer

Arlington, VA · On-site +1

$62K - $141K/yr

Experience with Agile engineering practices * TS/SCI clearance with a polygraph Clearance ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Engineer

Alexandria, VA · On-site

$62K - $141K/yr

Experience with Agile engineering practices * TS/SCI clearance with a polygraph Clearance ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Engineer

Chantilly, VA · On-site +1

$77K - $176K/yr

... data engineering activities on some of the most mission-driven projects in the industry. You'll ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Engineer

Chantilly, VA · On-site +1

$77K - $176K/yr

... data engineering activities on some of the most mission-driven projects in the industry. You'll ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Engineer, Mid

Mclean, VA · On-site

$62K - $141K/yr

... data engineering activities on some of the most mission-driven projects in the industry. You'll ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Engineer, Mid

Mclean, VA · On-site

$62K - $141K/yr

... data engineering activities on some of the most mission-driven projects in the industry. You'll ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

ETL Data Engineer

Mclean, VA · On-site +1

$62K - $141K/yr

... software engineering skills it takes to help identify potential risks, contribute to solution ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Data Engineer, Senior

Mclean, VA · On-site +1

$77K - $176K/yr

Experience with Agile engineering practices Clearance: Applicants selected will be subject to a ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

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Part Time Data Engineering information

What are the key skills and qualifications needed to thrive as a Part Time Data Engineer, and why are they important?

To thrive as a Part Time Data Engineer, you need proficiency in programming languages like Python or SQL, knowledge of database management, and a degree in computer science or a related field. Familiarity with data warehousing tools, ETL processes, and platforms such as AWS, Google Cloud, or Apache Spark is typically required. Strong problem-solving abilities, attention to detail, and effective communication help individuals excel in this flexible role. These skills ensure accurate data pipelines, efficient data processing, and successful collaboration with cross-functional teams, even in a part-time capacity.

What is a part-time data engineering job?

A part-time data engineering job involves working fewer hours than a full-time position, typically focusing on building and managing data pipelines, organizing data storage, and ensuring data quality for organizations. Part-time data engineers may work on specific projects or provide support to larger teams, often with flexible schedules. They use programming languages and tools like Python, SQL, and cloud platforms to move, transform, and optimize data. This role is ideal for those seeking work-life balance, students, or professionals looking to gain experience or supplement their income.

How does a part-time data engineering role typically balance project responsibilities with limited working hours?

In a part-time data engineering position, tasks are often scoped to fit within your available hours, focusing on specific projects or maintenance work rather than broader, ongoing initiatives. You’ll likely collaborate closely with full-time engineers to ensure hand-offs are smooth and that you’re aligned on priorities. Clear communication and proactive time management are essential, as you may need to coordinate across teams or adjust your workload to meet deadlines. Many organizations also provide flexible scheduling and clear documentation practices to help part-time team members stay integrated and productive.

What is the difference between Part Time Data Engineering vs Part Time Data Analysis?

AspectPart Time Data EngineeringPart Time Data Analysis
Required CredentialsTypically requires knowledge of SQL, Python, ETL tools, and cloud platformsRequires skills in SQL, Excel, data visualization tools, and basic statistical knowledge
Work EnvironmentOften involves building data pipelines, managing databases, and working with data infrastructureFocuses on interpreting data, creating reports, and providing insights
Employer & Industry UsageUsed in tech companies, finance, and e-commerce for data infrastructure rolesCommon in marketing, consulting, and business intelligence roles across industries

Part Time Data Engineering involves developing and maintaining data pipelines and infrastructure, requiring technical skills in programming and cloud platforms. In contrast, Part Time Data Analysis centers on interpreting data, creating reports, and providing insights, often using visualization tools. Both roles are essential in data-driven organizations but differ in technical complexity and focus.

What are the most commonly searched types of Data Engineering jobs in Virginia? The most popular types of Data Engineering jobs in Virginia are:
What cities in Virginia are hiring for Part Time Data Engineering jobs? Cities in Virginia with the most Part Time Data Engineering job openings:
Infographic showing various Part Time Data Engineering job openings in Virginia as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Fellow, Data Engineering

Systems Planning and Analysis

Alexandria, VA • On-site

$115K - $139K/yr

Full-time, Part-time

Medical, Life, Retirement

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.
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.
Responsibilities
The Data Engineering Fellow 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 CapabilityCreate 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 enterprise-wide decision-support 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 Information
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 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.