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Data Source Jobs in Virginia (NOW HIRING)

Coordinate across WDP lines of business (Acquisition, Procurement, Supply Chain, Finance) to link SC data with other domain data; manage the DSCA data source inventory and metadata lifecycle in ...

All-Source Analyst

Herndon, VA · On-site

$66K - $106K/yr

Perform data collection and analysis of intelligence from multiple and complex information/ data sources to include classified and unclassified sources, reports and databases. * Synthesize data into ...

The All-Source Analyst is responsible for processing complex data sets, identifying patterns ... Perform data collection and analysis of intelligence from multiple and complex information/ data ...

All-Source Analyst

Herndon, VA · On-site

$66K - $106K/yr

The All-Source Analyst is responsible for processing complex data sets, identifying patterns ... Perform data collection and analysis of intelligence from multiple and complex information/ data ...

The ideal candidate will have an active interest in working with open-source data to produce timely, cogent intelligence products that meet Defense Intelligence requirements while working within ...

... data based on impact to military operations by assisting installation in the development of all ... Additionally, the All Source Analyst will be responsible for the identification and assessment of ...

... data based on impact to military operations by assisting installation in the development of all ... Additionally, the All Source Analyst will be responsible for the identification and assessment of ...

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Data Source information

See Virginia salary details

$45.6K

$163.6K

$241.4K

How much do data source jobs pay per year?

As of Jun 10, 2026, the average yearly pay for data source 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 the key skills and qualifications needed to thrive as a Data Source, and why are they important?

To thrive as a Data Source, you need a comprehensive understanding of data collection, data integrity, and compliance with relevant data standards, often supported by experience in data management or information systems. Familiarity with database management systems, data warehousing tools, and data governance frameworks is typically required. Strong attention to detail, analytical thinking, and effective communication skills are essential soft skills for ensuring accurate and accessible data delivery. These abilities are crucial for maintaining data quality, supporting decision-making, and upholding organizational trust in information assets.

How do Data Source professionals typically collaborate with data engineers and analysts on large projects?

Data Source professionals play a key role in bridging the gap between raw data and actionable insights. They work closely with data engineers to ensure data is collected, integrated, and maintained accurately from multiple sources, while also collaborating with analysts to understand data requirements and support reporting needs. Regular communication and alignment meetings are common, and successful collaboration often involves clearly documenting data flows, troubleshooting data quality issues, and jointly developing data pipelines. This teamwork helps ensure that data is reliable, accessible, and tailored to the organization's analytical goals.

What is the difference between Data Source vs Data Analyst?

AspectData SourceData Analyst
Primary RoleProvides raw data for analysisInterprets and analyzes data to generate insights
Required SkillsData collection, database managementData analysis, visualization, reporting
Work EnvironmentData collection points, databases, data warehousesOffice, remote, analytics teams
CertificationsDatabase certifications, data managementExcel, SQL, data analysis certifications

In summary, a Data Source focuses on providing and managing raw data, while a Data Analyst interprets this data to support decision-making. Both roles are essential in the data ecosystem but serve different functions within the data workflow.

What are Data Sources?

Data sources are origins or locations from which data is obtained for analysis, reporting, or storage. They can include databases, spreadsheets, APIs, data warehouses, or even physical files. In technology and business contexts, a data source provides the raw information that systems and analysts use to make informed decisions or drive applications. Understanding the type and structure of a data source is crucial for effective data integration and management.
What are popular job titles related to Data Source jobs in Virginia? For Data Source jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Data Source jobs in Virginia look for? The top searched job categories for Data Source jobs in Virginia are:
Data Scientist (SME) - TS/SCI with Polygraph Required

Data Scientist (SME) - TS/SCI with Polygraph Required

Logistics Management Institute

Mclean, VA

Full-time

Posted 9 days ago


Job description

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.


Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

Position is on the research staff of a government consulting organization and will be based out of Reston, VA. This position provides verified mathematical and scientific techniques programmatically to answer questions prioritized by the Sponsor.


  • Work with a project-based team comprised of staff and other contractors.
  • Work closely with the Sponsor to review and track data science requirements and provide regular status updates.
  • Consult with customers to determine present and future user needs for Sponsor consideration.
  • Utilize project management systems such as a Content Management System (CMS) (e.g. Wordpress), Confluence and JIRA to define and track requirements.
  • Engage frequently with customers and stakeholders to clearly explain the project status and results in both written and verbal or multimedia briefings. 
  • Provide traceability within program documents and the overall computing environment and architecture.
  • Implement data science requirements, to include data engineering and data analytics services as defined by the Sponsor.
  • Use the full software lifecycle to create data science products which include data ingestion, analytics which may include machine learning, and some form of output as either a machine-readable format (e.g. file output, database output, standard/streaming output) or a user interface or dashboard.
  • Develop robust data engineering pipelines utilizing Apache Nifi and Python to include use and development of REST APIs and microservices.
  • Clean, parse and transform data from multiple file types into appropriate database architecture (e.g. SQL, noSQL, graph) which performs at scale.
  • Develop self-guided training curriculum which includes detailed Jupyter Notebooks and documentation about how to use open-source and commercial software and Sponsor-developed data science software.
  • Develop, deploy and provide feature enhancements using Python for data science products and services, to include Python packages, code documentation, notebooks, and microservices.

Required
  • Bachelor’s Degree in a quantitative discipline (e.g., related discipline)
  • Minimum 6-8 years experience
  • Demonstrated experience programming with Python.
  • Demonstrated experience with general Linux computing and advanced bash scripting.
  • Demonstrated experience constructing complex multi-data source queries with database technologies such as PostgreSQL, MySQL, Neo4J or RDS.
  • Demonstrated experience processing data sources containing structured or unstructured data.
  • Demonstrated experience developing data pipelines with NiFi to bring data into a central environment.
  • Demonstrated experience delivering results to stakeholders through written documentation and oral briefings.
  • Demonstrated experience using code repositories such as Git.
  • Demonstrated experience using Elastic and Kibana technologies.
  • Demonstrated experience working with multiple stakeholders.
  • Demonstrated experience documenting such artifacts as code, Python packages and methodologies.
  • Demonstrated experience using Jupyter Notebooks.
  • Demonstrated experience with machine learning techniques including natural language processing.
  • Demonstrated experience explaining complex technical issues to more junior data scientists, in graphical, verbal, or written formats.
  • Demonstrated experience developing tested, reusable and reproducible work.
  • Work or educational background in one or more of the following areas: mathematics, statistics, hard sciences (e.g. Physics, Computational Biology, Astronomy, Neuroscience, etc.) computer science, data science, or business analytics.
  • Must possess TS/SCI with polygraph.
Desired
  • Demonstrated experience with system configurations, development and design, specifically around enterprise systems.
  • Demonstrated experience communicating both verbally and in writing, when responding to emails, telephone calls and/or in person inquiries from organizational personnel.
  • Certification:
    • ISACA Certified Information Security Manager (CISM)
    • ISACA Certified Information Systems Auditor (CISA)
    • ISC Certified Information Systems Security Professional (CISSP)
    • ISC Certified Cloud Security Professional (CCSP)
    • ISC Certified Authorization Professional (CAP)

#LI-SH1

Target salary range: $104,040 - $183,600. Final compensation will be determined by a variety of factors including but not limited to your skills, experience, education, and/or certifications.

The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.

Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.