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Remote Database Engineer Jobs in Virginia (NOW HIRING)

IntelliTech

Senior Data AI Engineer

Alexandria, VA · On-site +1

$103.20K - $140.20K/yr

Remote Clearance: Active DoD Secret clearance required Employment Type: Full-Time (W-2) Citizenship ... Experience with MongoDB or other document-oriented databases, including data modeling and ...

TEKsystems

Systems Engineer

Herndon, VA · Remote

$80 - $89/hr

... Database Engineers, Cloud Operations Engineers, Tools Engineers, Application Developers, and ... remote position. Application Deadline This position is anticipated to close on May 28, 2026. About ...

VTG

Software Engineer

Chantilly, VA · Remote

Design and optimize high-performance graph databases containing tens of billions of edges ... Bachelor's degree in Geospatial Intelligence, Geography, Remote Sensing, Intelligence Studies ...

Ellucian Company LLC

Sr. Software Engineer

Reston, VA · Remote

$127.40K - $168K/yr

Drive change across the development lifecycle. 100% remote position. Requires a minimum of a ... Database Technologies: with normalized/denormalized databases, in Version Control & DevOps Tools ...

Imagineeer LLC

Data Migration Specialist

Arlington, VA · On-site +1

$135K - $145K/yr

Collaborate with software engineers, database administrators, and development teams to ensure ... This is a remote position. Compensation: $135,000.00 - $145,000.00 per year About Us Our Approach ...

Deloitte

AI and Data Science Engineer III

Richmond, VA · On-site +1

$113.30K - $136.10K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We ...

Deloitte

AI and Data Science Engineer III

Mclean, VA · On-site +1

$115.70K - $139K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We ...

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How much do remote database engineer jobs pay per hour?

As of May 30, 2026, the average hourly pay for remote database engineer in Virginia is $52.37, according to ZipRecruiter salary data. Most workers in this role earn between $42.12 and $58.75 per hour, depending on experience, location, and employer.

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

To thrive as a Remote Database Engineer, you need strong expertise in database design, optimization, and management, typically supported by a degree in computer science or a related field. Familiarity with database platforms like MySQL, PostgreSQL, Microsoft SQL Server, and cloud-based systems, along with certifications such as Oracle Certified Professional or AWS Certified Database - Specialty, is highly valued. Excellent problem-solving, communication, and self-management skills are crucial for collaborating across distributed teams and maintaining system reliability. These skills and qualities are important to ensure secure, efficient, and scalable database solutions in a remote work environment.

How does a Remote Database Engineer typically collaborate with development and operations teams to ensure database reliability?

As a Remote Database Engineer, you'll frequently coordinate with both development and operations teams through virtual meetings, collaborative platforms, and ticketing systems. Your main responsibilities include reviewing schema changes, optimizing queries, and troubleshooting performance issues alongside developers. You'll also work with operations staff to implement backup strategies, monitor database health, and ensure security compliance. Clear communication and proactive documentation are essential for seamless collaboration in a remote environment.

What is a Remote Database Engineer?

A Remote Database Engineer is a professional who designs, implements, maintains, and optimizes database systems while working from a location outside of a traditional office setting. Their responsibilities include ensuring database security, troubleshooting issues, managing backups, and improving performance, all while collaborating with other team members virtually. They often work with a range of database technologies such as SQL, NoSQL, and cloud-based solutions to support business applications and data needs.

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

AspectRemote Database EngineerRemote Data Analyst
Required CredentialsBachelor's in Computer Science, SQL, database certificationsBachelor's in Statistics, Data Science, SQL, Excel skills
Work EnvironmentDeveloping, maintaining, and optimizing databases remotelyAnalyzing data sets, creating reports remotely
Employer & Industry UsageTech, finance, healthcare companies managing data infrastructureMarketing, finance, consulting firms interpreting data trends

Remote Database Engineers focus on building and maintaining databases, requiring technical certifications and programming skills. Remote Data Analysts interpret data to inform business decisions, emphasizing analytical tools and reporting. Both roles are common in tech-driven industries and often overlap in data-related tasks, but they serve different core functions in data management and analysis.

What are the most commonly searched types of Database Engineer jobs in Virginia? The most popular types of Database Engineer jobs in Virginia are:
What are popular job titles related to Remote Database Engineer jobs in Virginia? For Remote Database Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Database Engineer jobs in Virginia look for? The top searched job categories for Remote Database Engineer jobs in Virginia are:
What cities in Virginia are hiring for Remote Database Engineer jobs? Cities in Virginia with the most Remote Database Engineer job openings:
Remote Database Engineer jobs near you
Infographic showing various Remote Database Engineer job openings in Virginia as of May 2026, with employment types broken down into 89% Full Time, 7% Part Time, and 4% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $108,939 per year, or $52.4 per hour.

Senior Data AI Engineer

IntelliTech

Alexandria, VA • On-site, Remote

$103.20K - $140.20K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 28 days ago

Job description

Location: Remote
Clearance: Active DoD Secret clearance required
Employment Type: Full-Time (W-2)
Citizenship: U.S. Citizenship required
IntelliTech is seeking a Senior Data / AI Engineer to support a Department of War program focused on operationalizing a Government-owned digital twin application for ammunition industrial base readiness. The platform is a supply chain simulation solution built on Python, FastAPI, and React that enables analysts to model production timelines, identify bottlenecks, assess supply chain risk, and evaluate surge and modernization scenarios.
This role will own the data lifecycle end-to-end-from raw file ingestion through validation, normalization, versioning, and delivery of run-ready artifacts to the simulation engine. The engineer will also help design and implement the AI-enabled decision-support layer, supporting natural-language analysis of scenario outputs, automated comparison and briefing generation, and guided scenario creation.
This is a hands-on role on a lean, senior team. The ideal candidate is comfortable writing production code daily, designing scalable data pipelines, and working directly with Government analysts and data stakeholders to deliver mission-focused solutions.Key ResponsibilitiesData Ingestion and Automation
  • Design and implement governed ingestion pipelines for complex defense supply chain datasets, including Bills of Materials (BOM), demand and order backlogs, facility and production line capacity, supplier risk, and acquisition planning data.
  • Build validation services that enforce schema conformance, referential integrity across linked datasets, circular reference detection, and business-rule validation with actionable row- and column-level feedback.
  • Implement raw data preservation in object storage such as Amazon S3, including metadata capture for source type, upload timestamp, uploader identity, file checksum, and dataset version.
  • Develop canonical data transformation workflows that convert validated source inputs into normalized, run-ready artifacts aligned to the simulation engine's entity model.
  • Implement dataset versioning and lineage tracking so each scenario run is tied to explicit input versions and assumptions.
Automated Data Refresh
  • Work with Government stakeholders and source-system owners to identify, prioritize, and implement automated or semi-automated data refresh paths.
  • Participate in Technical Exchange Meetings (TEMs) to help define data contracts, including source format, semantics, refresh cadence, and validation requirements.
  • Implement approved connection patterns such as scheduled file landing, secure file exchange (SFTP), API-based retrieval, and cloud-to-cloud transfer mechanisms.
  • Maintain hardened controlled upload workflows in parallel so mission operations are not dependent solely on external integrations or approvals.
AI-Enabled Decision Support
  • Build the AI integration layer within the FastAPI backend to broker access to Government-approved hosted LLM endpoints.
  • Implement scoped retrieval logic that constrains AI context to approved run artifacts, simulation outputs, and post-processed analytics.
  • Develop natural-language Q&A capabilities that allow analysts to query scenario results such as bottlenecks, supplier risks, and differences between runs.
  • Build guided scenario generation workflows that translate analyst intent into structured JSON scenario configurations for user review and approval before execution.
  • Implement AI-assisted comparison summaries and brief-ready output generation.
  • Enable function calling and tool-use patterns so the model can dynamically query backend APIs for scenario comparison, bottleneck analysis, production planning, and supply chain risk.
  • Ensure all AI interactions are audit-logged, role-scoped, and grounded in explicit scenario artifacts.
Deterministic Analytics and Reporting
  • Extend existing comparison capabilities to generate structured side-by-side scenario outputs with standardized metrics and deltas.
  • Build reusable templates for brief-ready outputs that reduce analyst time-to-brief.
  • Generate reproducible comparison artifacts and store them as part of the scenario run record.
Data Quality and Performance
  • Implement data quality monitoring and dashboards for ingestion success rates, validation outcomes, and overall pipeline health.
  • Optimize data preparation and post-processing workflows to reduce end-to-end scenario runtime.
  • Design and implement version-bounded caching strategies for validated inputs, normalized data products, and reusable post-processing summaries.
Required Qualifications
  • Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related technical discipline and 8+ years of relevant experience; or Master's degree in a related field and 6+ years of relevant experience.
  • Active DoD Secret clearance.
  • 7+ years of professional experience in data engineering or data / AI engineering roles.
  • Strong hands-on Python development experience, including Pandas, NumPy, ETL/ELT design, data pipeline development, and asynchronous programming patterns.
  • Experience building data validation and quality frameworks, including schema enforcement, referential integrity, data contracts, and validation feedback mechanisms.
  • Experience integrating LLM APIs such as OpenAI, Anthropic, or equivalent platforms, including function calling, tool use, scoped retrieval, and prompt engineering for structured outputs.
  • Experience with MongoDB or other document-oriented databases, including data modeling and aggregation pipelines for analytics workloads.
  • Experience with Amazon S3 or other cloud object storage services, including raw, normalized, and curated data layering approaches.
  • Experience supporting DoD or federal Government programs.
  • Strong communication skills and the ability to work directly with technical and non-technical stakeholders in mission environments.
Preferred Qualifications
  • Experience with defense supply chain, logistics, manufacturing, or industrial base data.
  • Familiarity with Databricks, data mesh, or medallion architecture patterns such as bronze/silver/gold.
  • Familiarity with SimPy or discrete-event simulation data inputs and outputs.
  • Experience with Advana, WDP (War Data Platform), or other DoD enterprise data platforms.
  • Experience establishing data-sharing agreements and supporting Technical Exchange Meetings with Government source-system owners.
  • Knowledge of munitions-related data structures such as NIIN, CAGE, Bill of Material hierarchies, and production line capacity models.
  • Experience with Redis or other caching layers supporting analytics applications.
  • Experience with FastAPI or Flask backend development.
  • Prior experience supporting Army Cloud Environments
Tech Stack
  • Data Engineering: Python 3.11+, Pandas, NumPy
  • Backend: FastAPI, Motor (async MongoDB)
  • AI / LLM: OpenAI API or Government-approved hosted endpoint, function calling, scoped retrieval, prompt engineering
  • Database: MongoDB / Amazon DocumentDB /
  • Storage: Amazon S3
  • Cache: Redis / Amazon ElastiCache
  • Data Formats: Excel (.xlsx), JSON, CSV, SFTP, REST / SOAP APIs
  • Observability: Pipeline instrumentation, logging, and data quality metrics
Interview Process
Video interview required and may include a technical assessment.
Candidates should be prepared to discuss:
  • their hands-on experience building data pipelines, validation frameworks, and AI-enabled backend services
  • examples of systems or applications they have built from scratch
  • how they have handled data quality, lineage, and reproducibility in production environments
  • their experience integrating LLMs, retrieval workflows, and backend APIs into operational use cases
  • their work with large-scale or mission-critical federal datasets and analytics platforms
  • their availability to support periodic on-site work in the Washington, DC Metro Area or other Government locations as needed
Compensation and Benefits
IntelliTech is committed to fair and equitable compensation practices. The salary range for this position is $150,000 - $200,000. Actual compensation packages are based on several factors unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on these factors, IntelliTech utilizes the full width of the salary range.
IntelliTech provides a comprehensive benefits package designed to support employees' well-being and professional growth, including health insurance, dental insurance, and vision insurance, a 401(k), paid time off, professional development opportunities, and flexible work arrangements to support work-life balance.About IntelliTech
IntelliTech is a dynamic and forward-thinking small business specializing in Full Stack Engineering, Data Analytics, Cloud Solutions, and DevSecOps services. Our mission is to empower government and commercial clients to solve complex technical challenges through practical, innovative, and mission-focused engineering solutions.Equal Opportunity Employer
At IntelliTech, we are committed to building a diverse and inclusive workplace. We believe that a variety of perspectives and backgrounds leads to stronger teams and better solutions. IntelliTech is an Equal Opportunity Employer and does not discriminate on the basis of race, religion, gender, age, disability, or veteran status. We encourage all qualified candidates to apply.

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