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Full Stack Data Analyst Jobs in Virginia (NOW HIRING)

Full Stack Developer

Arlington, VA · On-site

$150K - $200K/yr

Develop full-stack features with strong focus on Python backend development ... Build user interfaces for real-time data visualization from sensor feeds * Implement backend ...

Senior Full-Stack Developer (Python / Django / AWS) Location: Remote (EST Preferred) Type: Contract ... Design and manage relational data models and ensure efficient data access patterns * Build and ...

Design, develop, test, and maintain full-stack applications (UI, service/API layer, and data access layer) in an Agile delivery environment. * Participate in software programming initiatives to ...

Our engineers work to collect, process, and feed analytic tools, turning data into intelligence in ... The Full Stack Developer participates in development efforts to deliver a complete software ...

... analytic applications. This role involves collaborating with cyber SMEs, data scientists, and ... in full-stack and UI development, or equivalent practical experience, with a STEM degree (field ...

... analytic applications. This role involves collaborating with cyber SMEs, data scientists, and ... in full-stack and UI development, or equivalent practical experience, with a STEM degree (field ...

... analytic applications. This role involves collaborating with cyber SMEs, data scientists, and ... in full-stack and UI development, or equivalent practical experience, with a STEM degree (field ...

The ideal candidate will also have an analytical mindset and a keen eye for detail. The goal is to ... Proven experience as an Full Stack Developer * Experience in designing and building applications

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Showing results 1-20

Full Stack Data Analyst information

See Virginia salary details

$33.7K

$81.9K

$134.8K

How much do full stack data analyst jobs pay per year?

As of Jul 14, 2026, the average yearly pay for full stack 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 the difference between Full Stack Data Analyst vs Data Scientist?

AspectFull Stack Data AnalystData Scientist
Required SkillsData analysis, visualization, basic programming, SQL, reportingAdvanced programming, statistical modeling, machine learning, data engineering
Work EnvironmentBusiness teams, analytics departments, reporting toolsResearch teams, data science departments, AI/ML projects
CertificationsData analysis, SQL, Excel certificationsData science, machine learning, Python/R certifications
Industry UsageBusiness intelligence, marketing, financeResearch, AI development, predictive modeling

While both roles involve working with data, Full Stack Data Analysts focus on end-to-end data analysis and reporting within business contexts, whereas Data Scientists develop advanced models and algorithms for predictive insights. The roles often overlap in skills like SQL and programming, but Data Scientists typically require deeper expertise in statistical methods and machine learning.

What are popular job titles related to Full Stack Data Analyst jobs in Virginia? For Full Stack Data Analyst jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Full Stack Data Analyst jobs in Virginia look for? The top searched job categories for Full Stack Data Analyst jobs in Virginia are:
What cities in Virginia are hiring for Full Stack Data Analyst jobs? Cities in Virginia with the most Full Stack Data Analyst job openings:
Infographic showing various Full Stack Data Analyst job openings in Virginia as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 86% Full Time, 6% Part Time, 1% Temporary, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $81,931 per year, or $39.4 per hour.

Software Engineer (Full Stack) - SME

GRVTY

Springfield, VA • Remote

Other

Re-posted 20 days ago


Job description

What Impact You'll Have:

Join a mission-focused team where your work directly supports critical national security objectives. We are seeking a Subject Matter Expert (SME) Full Stack Developer to lead the design, development, and delivery of scalable, mission-driven applications within an ML/Ops environment. This role combines deep technical expertise with advanced system-level thinking and close collaboration across engineering, data science, and customer stakeholder teams.

The Full Stack Developer will perform rapid application design, ETL, data analysis, and interpretation while developing rules and methodologies for data collection and analysis. You will architect, develop, and maintain a Python-based data warehouse processing system that serves as the backend for a user-facing application, while also leading development of modern GUI applications using REST APIs and contemporary web frameworks.

You will work closely with data scientists, computer vision engineers, ETL engineers, and intelligence analysts to integrate machine learning capabilities into production systems, enabling scalable model deployment, monitoring, and continuous improvement. This role emphasizes ownership, technical leadership, and delivery of production-ready solutions that operate reliably in dynamic, real-world environments.

What You'll Be Owning:

Lead and participate in the architectural design of complex features early in the development lifecycle.
Translate customer requirements and roadmap priorities into technical solutions, tasks, timelines, and resource plans.
Develop, integrate, and maintain full stack applications supporting ML/Ops pipelines and data-driven systems.
Design and implement scalable APIs and services to support machine learning model deployment and inference.
Develop and maintain data pipelines, ETL processes, and data storage solutions for large-scale datasets.
Collaborate with data scientists and ML engineers to operationalize models within production environments.
Optimize application and system performance for scalability, reliability, and efficiency, including edge and distributed environments when applicable.
Conduct peer reviews and establish coding standards to improve overall code quality and maintainability.
Guide development testing, exploratory testing, automated testing, and validation strategies.
Own code in production environments, respond to incidents, and lead root cause analysis and continuous improvement efforts.
Ensure security, compliance, and governance are maintained throughout the development lifecycle.
Perform technical planning, system integration, verification and validation, and risk assessments across system components.
Mentor and develop junior and mid-level engineers, fostering technical growth and high-performing teams.
Drive adoption of modern ML/Ops practices, tools, and automation frameworks across the team.

What You Must Have:

Active TS/SCI clearance with the ability to obtain a CI poly
Bachelor's degree in Computer Science, Engineering, or a related technical field.
14+ years of professional experience in full stack software development.
Expert-level proficiency in Python and object-oriented design patterns.
Extensive experience developing backend systems, APIs, and data processing pipelines.
Strong experience with modern web development frameworks, including React.js, Node.js, and/or Electron.
Deep understanding of data modeling techniques and experience working with large-scale and time series datasets.
Experience with relational and non-relational databases such as PostgreSQL, MongoDB, and BigQuery.
Experience building and maintaining RESTful APIs and microservices architectures.
Experience supporting machine learning workflows, including model integration, deployment, and monitoring.
Familiarity with ML/Ops tools and utilities such as MLflow, DVC, and/or Optuna.
Strong experience with Python libraries such as NumPy and Pandas.
Experience with Python web frameworks such as Flask, FastAPI, Pydantic, Gunicorn, and Uvicorn.
Experience with containerization and DevOps practices, including Docker and CI/CD pipelines.
Experience with web servers such as Apache and Nginx.
Experience working within Agile development environments and using associated tools.

What Would be Nice to Have:

Experience supporting government or defense-related programs.
Experience integrating computer vision or machine learning capabilities into operational systems.
Knowledge of real-time data processing, streaming architectures, or distributed systems.
Experience with cloud-based ML/Ops environments and infrastructure (AWS, Azure, or Google Cloud Platform).
Experience with parallelization and multiprocessing frameworks such as Dask.
Knowledge of geospatial data processing tools and libraries including GeoPandas, Shapely, Rasterio, QGIS, and ArcPy.
Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
Experience with remote procedure call technologies such as gRPC and JSON-RPC.

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