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Remote Data Jobs in Virginia (NOW HIRING)

Data Architect

Leesburg, VA · On-site +1

$64.50 - $83/hr

This opportunity is 100% remote. Key Responsibilities Enterprise Data Architecture & Engineering * Design and implement scalable enterprise data architectures leveraging AWS and Apache ecosystem ...

Engineering Data Scientist

Lynchburg, VA · On-site +1

$62K - $97K/yr

BWXT is currently seeking a Engineering Data Scientist for its Lynchburg, VA location with some remote work! BWXT is People Strong, Innovation Driven - be part of BWXT's innovation hub. BWXT ...

Engineering Data Scientist

Lynchburg, VA · On-site +1

$62K - $97K/yr

BWXT is currently seeking a Engineering Data Scientist for its Lynchburg, VA location with some remote work! BWXT is People Strong, Innovation Driven - be part of BWXT's innovation hub. BWXT ...

The Data Analysis- Senior,leads the integration and application of advanced data analytics to solve ... Remote View, ERDAS Imagine, Macromedia Dreamweaver, Macromedia Fireworks, Photoshop, HTML, and ...

Data Scientist

Mclean, VA · On-site +1

$200K - $240K/yr

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a Data Scientist to join our team to provide support specializing in natural language(NLP) processing and associated data ...

Data Scientist

Mclean, VA · On-site +1

$200K - $240K/yr

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a Data Scientist to join our team to provide Subject Matter expertise and support specializing in natural language(NLP ...

Data Architect

Arlington, VA · On-site +1

$145K - $165K/yr

Data Employment Type: Full Time Location ... Remote Compensation: $145,000 - $165,000 / year Description At Nüvitek, customer success is our ...

Data Analyst About the Organization Now is a great time to join Redhorse Corporation. Our mission ... for remote work to be determined by the program manager and customer. Essential Functions:

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Showing results 1-20

Remote Data information

See Virginia salary details

$45.6K

$163.6K

$241.4K

How much do remote data jobs pay per year?

As of Jul 14, 2026, the average yearly pay for remote data in Virginia is $163,603.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,400.00 and $168,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced when working as a Remote Data Analyst, and how can they be addressed?

Remote Data Analysts often face challenges such as maintaining effective communication with team members, managing access to secure data, and staying aligned with project goals across different time zones. These can be addressed by leveraging collaboration tools like Slack or Microsoft Teams, following strict data security protocols, and participating in regular virtual meetings to ensure everyone is on the same page. Proactive communication and strong organizational skills are key to thriving in a remote data role.

What is the difference between Remote Data vs Remote Data Analyst?

AspectRemote DataRemote Data Analyst
Required CredentialsBachelor's in Data Science, Computer Science, or related field; knowledge of databases and data toolsBachelor's in Data Science, Statistics, or related; proficiency in data analysis tools like Excel, SQL, and visualization software
Work EnvironmentRemote, often independent, with collaboration via online platformsRemote, involves analyzing data sets, creating reports, and communicating findings
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceBusiness, marketing, finance, and tech sectors

Remote Data generally refers to roles focused on managing and processing data, while Remote Data Analyst emphasizes analyzing data to generate insights. Both roles often require similar educational backgrounds and work remotely, but Data Analysts typically focus more on interpreting data and creating reports for decision-making.

How can I make 2000 a week working from home?

Remote data roles such as data analyst or data scientist can offer high earning potential, with experienced professionals earning $2,000 or more weekly through project-based work, consulting, or full-time employment. Building skills in data analysis tools, programming languages, and obtaining relevant certifications can help increase earning capacity, especially when working independently or in specialized niches.

Are there real remote data entry jobs?

Yes, remote data entry jobs are available and involve inputting information into digital systems from home. These roles typically require basic computer skills, attention to detail, and sometimes familiarity with spreadsheet or database software. Legitimate positions are often posted on reputable job boards and do not require upfront fees.

How to make $1000 a week remotely?

Remote data roles such as data analyst or data scientist can generate $1000 or more weekly with experience, strong analytical skills, and proficiency in tools like Excel, SQL, or Python. Achieving this income often involves freelance projects, contract work, or full-time positions with high pay rates, and may require certifications or specialized knowledge in data management and analysis.

What are the key skills and qualifications needed to thrive as a Remote Data Analyst, and why are they important?

To thrive as a Remote Data Analyst, you need strong analytical skills, proficiency in statistics, and a background in data science or a related field. Familiarity with data analysis tools such as Python, R, SQL, and platforms like Tableau or Power BI, along with relevant certifications, is typically required. Excellent self-motivation, time management, and communication skills help you stand out in a remote environment. These capabilities are crucial for delivering accurate insights, collaborating effectively from a distance, and meeting business objectives efficiently.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

What are remote data jobs?

Remote data jobs are positions that involve collecting, analyzing, managing, or interpreting data while working from a location outside the traditional office environment. These roles can include data analysts, data scientists, data entry specialists, and database administrators, among others. Remote data professionals use online tools and platforms to access and process data, collaborate with teams, and deliver insights or reports. This flexible work arrangement allows individuals to contribute to data-driven projects from anywhere with an internet connection.
What are the most commonly searched types of Data jobs in Virginia? The most popular types of Data jobs in Virginia are:
What cities in Virginia are hiring for Remote Data jobs? Cities in Virginia with the most Remote Data job openings:
Data Architect

Data Architect

Anika Systems

Leesburg, VA • On-site, Remote

$64.50 - $83/hr

Full-time

Re-posted 21 days ago


Job description

Anika Systems is seeking a highly skilled Data Architect to lead the design and implementation of enterprise data architectures supporting federal clients. This role will be instrumental in shaping data strategy, enabling data-driven decision-making, and supporting the establishment and maturation of Office of the Chief Data Officer (OCDO) organizations.
The ideal candidate brings deep expertise in enterprise data modeling, cloud-based data platforms, metadata management, and data governance, along with hands-on experience applying AI/ML, Knowledge Graphs, and semantic technologies to modern data ecosystems. This role requires a forward-thinking architect who embraces AI-driven development workflows and can integrate emerging techniques such as GraphRAG into enterprise data platforms.
This opportunity is 100% remote.
Key Responsibilities
Enterprise Data Architecture & Engineering
  • Design and implement scalable enterprise data architectures leveraging AWS and Apache ecosystem technologies (e.g., Spark, Iceberg).
  • Architect modern AI-enabled data platforms, including support for machine learning, LLM integration, and retrieval-augmented generation (RAG) patterns.
  • Develop and maintain conceptual, logical, and physical data models, including Entity Relationship Diagrams (ERDs).
  • Architect modern data lakehouse and data warehouse solutions using Apache Iceberg and cloud-native services.
  • Define and enforce standards for data integration, data quality, and data lifecycle management.
  • Design and implement Knowledge Graph architectures, integrating structured and unstructured data sources.
AI, Knowledge Graphs & Semantic Architecture
  • Design and implement Knowledge Graphs and semantic data layers using ontologies, taxonomies, and linked data principles.
  • Apply GraphRAG architectures to enhance LLM-based applications with context-aware, explainable data retrieval.
  • Develop and manage ontologies and semantic models to enable interoperability, data discovery, and advanced analytics.
  • Integrate AI/ML and generative AI capabilities into enterprise data ecosystems, including vector databases and embedding pipelines.
  • Leverage AI-assisted development tools (e.g., code generation, data pipeline automation, metadata enrichment) to improve delivery speed and quality.
  • Ensure alignment between data architecture and AI governance, including model transparency, traceability, and responsible AI practices.
Metadata, Data Catalog, and Data Management
  • Establish and manage enterprise metadata frameworks, including data dictionaries, business glossaries, and technical metadata repositories.
  • Support implementation or optimization of Enterprise Data Resource Management Systems (EDRMS) and data catalog tools (e.g., Collibra, ServiceNow, or similar platforms).
  • Ensure referential integrity and traceability between data assets, metadata, ontologies, and enterprise data initiatives.
  • Design systems that enable data lineage, observability, and quality monitoring, including AI-generated metadata and lineage tracking.
Stakeholder Engagement & Data Governance
  • Lead or support stakeholder listening campaigns to gather input from executives, data leaders, and practitioners across the enterprise.
  • Collaborate with stakeholders to identify data challenges, AI use cases, and opportunities for advanced analytics and automation.
  • Support the development and maintenance of data governance frameworks, policies, and standards, including AI and semantic governance.
  • Maintain and prioritize a data initiatives backlog, ensuring alignment with mission needs and stakeholder priorities.
Agile Delivery & Continuous Improvement
  • Work within Agile frameworks to iteratively deliver data architecture and AI-enabled solutions.
  • Support analysis of alternatives (AoA) for data and AI tools/platforms, providing recommendations based on cost, capability, and mission fit.
  • Track and report on data strategy progress, maturity improvements, and program outcomes.
  • Continuously refine data architecture based on stakeholder feedback, emerging AI capabilities, and evolving organizational needs.
Required Qualifications
  • Bachelor's degree in Computer Science, Information Systems, Data Science, or related field or comparable experience.
  • 8+ years of experience in data architecture, data engineering, or enterprise data management.
  • Demonstrated experience integrating AI/ML or generative AI capabilities into data platforms.
  • Hands-on experience with:
    • AWS data services (e.g., S3, Glue, Redshift, Lake Formation)
    • Apache technologies (e.g., Spark, Iceberg, Hive)
    • Relational databases
  • Strong expertise in data modeling and ERD development.
  • Experience designing or implementing Knowledge Graphs, ontologies, or semantic data models.
  • Familiarity with Graph-based retrieval approaches (e.g., GraphRAG or similar patterns).
  • Experience implementing metadata management, data cataloging, and data governance solutions.
  • Demonstrated experience supporting federal data strategy initiatives or OCDO organizations.
  • Strong understanding of data quality, lineage, observability, and AI data readiness frameworks.
  • Proficiency with AI-assisted tools and workflows (e.g., LLM copilots, automated code generation, data augmentation tools).
  • Ability to communicate complex technical concepts to non-technical stakeholders.
  • U.S. Citizenship required; ability to obtain and maintain a federal clearance.
Preferred Qualifications
  • Experience supporting agencies such as SEC, DHS, Treasury, or Federal Reserve System.
  • Familiarity with Evidence Act, Federal Data Strategy, and CDO Council guidance.
  • Experience with Collibra, Informatica, Alation, or similar data catalog tools.
  • Experience with graph databases (e.g., Neo4j, Amazon Neptune) and vector databases.
  • Knowledge of data maturity frameworks (e.g., EDM DCAM, TDWI).
  • AWS certifications or data architecture certifications.
  • Experience implementing RAG or GraphRAG solutions in production environments.
  • Familiarity with semantic web standards (RDF, OWL, SPARQL).