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Remote Data Manager Jobs in Virginia (NOW HIRING)

Data Engineer III

Mclean, VA ยท Remote

$115K - $139K/yr

Data Engineer III Job number: 820 This is a remote position. Ad Hoc is a technology company that ... Our customers include NASA, the General Services Administration, Office of Personnel Management ...

Scientific Data Analyst

Vienna, VA ยท Remote

$85K - $115K/yr

This role will be 100% remote for the foreseeable future. In this role, you will manage and analyze quantitative epidemiological, clinical and/or behavioral data and provide output in the format ...

... Data Visualization Specialist to support KPS and our government customer. The position is remote ... Design and maintain operational dashboards for grant management, including performance metrics ...

New

Management is hands off, gives the team the freedom to explore new approaches, and markets the best ... remote work) and requires a TS/SCI + Poly clearance (acceptable to this customer). What You'll be ...

Data Engineer

Centreville, VA ยท On-site +1

$113K - $136K/yr

Data Management & Optimization * Collect, clean, and validate large volumes of structured and ... Schedules (Remote / Hybrid) - - Medical / Dental / Vision / Flexible Spending Account (FSA ...

TS/SCI with Poly Potential for Remote Work: ORA_ON_SITE Description The Data Scientist will apply ... Collaborate with project requestors, stakeholders, and project managers to refine project requests ...

Data Engineer

Arlington, VA ยท Remote

$131K - $158K/yr

This is a fully remote position. Here, your work is more than a job - it's a journey in innovation ... Knowledge of database management systems (PostgreSQL, SQL Server, DynamoDB, MongoDB) * Familiarity ...

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Remote Data Manager information

See Virginia salary details

$25.8K

$98.6K

$173.3K

How much do remote data manager jobs pay per year?

As of Jun 25, 2026, the average yearly pay for remote data manager in Virginia is $98,566.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,200.00 and $127,000.00 per year, depending on experience, location, and employer.

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

AspectRemote Data ManagerData Analyst
Required CredentialsBachelor's in IT, Data Science, or related field; experience with database managementBachelor's in Statistics, Mathematics, or related field; proficiency in data visualization tools
Work EnvironmentRemote, often within IT or data teamsRemote or on-site, within business or research teams
Employer & Industry UsageTech companies, healthcare, finance, where data management is criticalMarketing, finance, consulting, analyzing data trends

Remote Data Managers focus on maintaining and organizing data systems, ensuring data integrity, and managing databases remotely. Data Analysts interpret data, generate reports, and provide insights. While both roles work with data, the Remote Data Manager handles data infrastructure, whereas Data Analysts focus on analyzing data to support decision-making.

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

To thrive as a Remote Data Manager, you need a solid background in data management, database administration, and data analysis, typically supported by a degree in computer science or a related field. Expertise in tools such as SQL, data visualization platforms (e.g., Tableau or Power BI), and familiarity with data privacy regulations are commonly required, along with relevant certifications like CDMP or PMP. Strong organizational skills, attention to detail, and effective remote communication abilities set outstanding candidates apart. These skills ensure data integrity, facilitate collaboration across distributed teams, and drive data-driven decision-making within organizations.

What is a Remote Data Manager?

A Remote Data Manager is a professional responsible for overseeing the collection, storage, organization, and analysis of data for an organization, while working from a location outside of a traditional office. They ensure data integrity, security, and compliance with relevant regulations. Their duties often include managing databases, setting data policies, and collaborating with teams to support data-driven decision making. Remote Data Managers use various digital tools to communicate and manage data remotely, making this role ideal for those seeking flexible work arrangements.

What are some typical challenges faced by Remote Data Managers when coordinating with cross-functional teams?

Remote Data Managers often need to collaborate with teams across different departments and time zones, which can make communication and project alignment challenging. They may face difficulties in ensuring data consistency, timely updates, and maintaining data security standards when team members are dispersed. Effective use of collaboration tools, clear documentation, and regular virtual meetings are essential to overcome these challenges and ensure smooth operations.
What job categories do people searching Remote Data Manager jobs in Virginia look for? The top searched job categories for Remote Data Manager jobs in Virginia are:
What cities in Virginia are hiring for Remote Data Manager jobs? Cities in Virginia with the most Remote Data Manager job openings:
Infographic showing various Remote Data Manager job openings in Virginia as of June 2026, with employment types broken down into 83% Full Time, 6% Part Time, and 11% Contract. Highlights an 4% In-person, and 96% Remote job distribution, with an average salary of $98,566 per year, or $47.4 per hour.
Public Health Data Analyst

Public Health Data Analyst

CyberData Technologies

Herndon, VA โ€ข Remote

Full-time

Posted 15 days ago


Job description


Public Health Data Analyst
DNPAO Data Analysis and Management Project

Location: Remote (Atlanta Metropolitan Area Preferred)

*** Must be able to Obtain and Maintain a CDC Public Trust Clearance ***


Job Description

CyberData Technologies is seeking an experienced Public Health Data Analyst to support the Centers for Disease Control and Prevention (CDC), Division of Nutrition, Physical Activity, and Obesity (DNPAO). The selected candidate will provide advanced data management, statistical analysis, and epidemiologic support for public health initiatives focused primarily on breastfeeding, child nutrition, obesity prevention, and related chronic disease prevention programs. This position will support DNPAO's efforts to generate high-quality, reproducible analyses and reports using large national public health datasets. The successful candidate will create and manage complex data systems, develop statistical analysis plans, perform sophisticated epidemiologic analyses, and communicate findings that inform public health programs, policy decisions, and national surveillance activities. The ideal candidate will possess extensive experience working with complex survey data, large public health datasets, advanced statistical methods, and data management practices within federal public health environments.


Job Responsibilities

Data Analysis Planning

  • Develop comprehensive statistical analysis plans that support epidemiologic research and surveillance activities.
  • Identify research questions and hypotheses aligned with programmatic and policy objectives.
  • Determine appropriate inclusion and exclusion criteria for analyses.
  • Evaluate datasets and identify variables necessary to address research objectives.
  • Select appropriate statistical methodologies and software tools to support analyses.
  • Develop table shells, data specifications, and documentation supporting analytical activities.
  • Document all data preparation, transformation, and analytical processes to ensure reproducibility and transparency.

Data Management

  • Collect, review, code, validate, manipulate, and maintain large public health datasets.
  • Create and maintain data dictionaries and metadata documentation.
  • Develop and manage working datasets and analysis files.
  • Perform data cleaning, quality assurance, validation, and integrity checks.
  • Manage data related to breastfeeding, child nutrition, obesity, and other DNPAO program areas.
  • Maintain and analyze data from national surveillance systems and public-use datasets.
  • Access and utilize data files, questionnaires, and documentation from CDC and National Center for Health Statistics (NCHS) data collection systems.

Statistical Analysis and Interpretation

  • Conduct univariable, bivariable, and multivariable statistical analyses using complex survey data methodologies.
  • Analyze large national datasets and interpret findings for technical and non-technical audiences.
  • Produce recurring surveillance reports, statistical summaries, dashboards, and data visualizations.
  • Support annual Healthy People 2030 reporting activities related to maternal and child health indicators.
  • Develop quarterly updates for DNPAO Data, Trends, and Maps reporting systems.
  • Respond to federal partner requests, state-level inquiries, and ad hoc data requests.
  • Conduct analyses using longitudinal and cross-sectional datasets to support public health decision-making.
  • Prepare technical reports, manuscripts, presentations, and summary documents communicating analytical findings.
  • Collaborate with CDC scientists, epidemiologists, program staff, and external stakeholders to support surveillance and evaluation activities.

Public Health Surveillance Support

  • Support analyses involving national public health surveillance systems and large-scale survey datasets.
  • Provide technical expertise related to breastfeeding surveillance, nutrition monitoring, obesity prevention, physical activity, and maternal and child health indicators.
  • Assist in developing evidence-based recommendations that support public health programs and policy initiatives.
  • Ensure analytical methods adhere to CDC standards and best practices for complex survey analysis.

Required Skills and Experience

  • Master's degree or higher in Epidemiology, Biostatistics, Public Health, Statistics, Data Science, Health Sciences, or a related quantitative field.
  • Minimum of three (3) years of professional experience supporting epidemiologic research, public health surveillance, statistical analysis, or related analytical activities.
  • Advanced expertise using statistical software including SAS, SPSS, R, SUDAAN, Epi Info, or similar analytical tools.
  • Extensive experience managing and analyzing large, complex survey datasets that utilize weighting, clustering, and stratification methodologies.
  • Strong knowledge of epidemiologic methods, surveillance systems, and quantitative public health research.
  • Demonstrated experience developing statistical analysis plans and managing large datasets from acquisition through reporting.
  • Experience conducting multivariable statistical analyses and interpreting findings for public health applications.
  • Ability to independently manage multiple analytical projects and respond to ad hoc data requests.
  • Strong written and verbal communication skills, including technical report development and presentation of findings.
  • Experience developing reproducible analytical workflows and maintaining detailed documentation.

Preferred Skills and Experience

  • Experience supporting the Centers for Disease Control and Prevention (CDC) or other federal public health agencies.
  • Experience analyzing National Health and Nutrition Examination Survey (NHANES) data.
  • Experience working with the National Immunization Survey (NIS), National Survey of Childrenโ€™s Health, National Vital Statistics System (NVSS), Youth Risk Behavior Surveillance System (YRBSS), or similar national surveillance systems.
  • Knowledge of breastfeeding surveillance, maternal and child health, nutrition, obesity prevention, and chronic disease epidemiology.
  • Experience supporting Healthy People objectives, public health surveillance reporting, and policy-related analyses.
  • Familiarity with CDC data management standards and public-use datasets.
  • Experience developing data visualizations, dashboards, and automated reporting processes.
  • Experience working with Azure products (i.e. Databricks), Python and GitHub.