ZipRecruiter

Log In

1

Student Shadow Data Analytics Jobs in Reston, VA

Shadow Objects

Data Analytics Engineer

Washington, DC · Remote

$129K - $155K/yr

Data Analytics Engineer Clearance Requirement: Active DoD Secret Clearance required Location: Remote / Pentagon Position Overview The Data Analytics Engineer is a hybrid role combining Data Analyst ...

Sallie_mae

Manager, Data Analytics

Sterling, VA · On-site

Students need guidance navigating this important time in their life. They need someone who ... Analyze complex data sets to identify patterns and trends that will drive business growth.

Insilico Logix

Data Analyst

Herndon, VA

$60K - $70K/yr

... for OPT students and visa holders - Skills Enhancement Data Analytics Training Program is provided for selected candidates ** OPT students may also apply If you are qualified and interested in ...

Guidehouse

FM Data Analysis Specialist

Mclean, VA · On-site

ONE (1) year+ experience in financial management and data analytics What Would Be Nice To Have ... Student Loan PayDown * Tuition Reimbursement, Personal Development & Learning Opportunities

Guidehouse

FM Data Analysis Specialist

Mclean, VA

ONE (1) year+ experience in financial management and data analytics What Would Be Nice To Have ... Student Loan PayDown * Tuition Reimbursement, Personal Development & Learning Opportunities

next page

Showing results 1-20

All JobsStudent Shadow Data Analytics JobsStudent Shadow Data Analytics Jobs in Reston, VA

Student Shadow Data Analytics information

See Reston, VA salary details

$34.3K

$84.8K

$145.6K

How much do student shadow data analytics jobs pay per year?

As of Jun 19, 2026, the average yearly pay for student shadow data analytics in Reston, VA is $84,808.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,900.00 and $100,400.00 per year, depending on experience, location, and employer.

What are Student Shadow Data Analytics?

Student Shadow Data Analytics refers to the process of collecting and analyzing data about students as they are observed or 'shadowed' through their daily academic activities. This analysis helps educators and administrators understand student behaviors, learning patterns, and engagement levels. Insights from this data can be used to improve teaching strategies, personalize learning experiences, and identify areas where students may need additional support. Student shadowing combined with data analytics provides a comprehensive view of the student experience in educational settings.

What types of projects or tasks can I expect to work on as a Student Shadow in Data Analytics?

As a Student Shadow in Data Analytics, you will typically observe and assist with projects such as data collection, cleaning, and visualization. You might help analyze datasets to uncover trends or support team members in preparing reports and presentations for stakeholders. This role often involves collaborating closely with experienced data analysts and learning how to use industry-standard tools like Excel, SQL, or Python. It's a great opportunity to see how real-world business problems are solved using data-driven approaches.

What is the difference between Student Shadow Data Analytics vs Data Analyst?

AspectStudent Shadow Data AnalyticsData Analyst
Required CredentialsTypically enrolled in a related degree program, no formal certification requiredBachelor's degree in data science, statistics, or related field; certifications like SQL or Tableau often preferred
Work EnvironmentObservational role, often unpaid or internship-based, in educational or entry-level settingsFull-time professional role in corporate, finance, healthcare, or tech industries
Employer & Industry UsageEducational institutions, internships, entry-level projectsBusinesses, consulting firms, government agencies
Common Search & ComparisonYesYes

The main difference between Student Shadow Data Analytics and Data Analyst lies in experience, credentials, and work environment. Student Shadow roles are typically observational or internship-based, focusing on learning, while Data Analysts are full-time professionals performing data analysis tasks in various industries.

Do job shadows get paid?

Job shadows, including those in data analytics, are typically unpaid opportunities that allow students to observe professionals and learn about the field. Some organizations may offer stipends or incentives, but most shadowing experiences are voluntary and unpaid. It is important to confirm specific arrangements with the hosting organization.

Is AI replacing data analysts?

AI is automating certain tasks within data analysis, such as data cleaning and basic reporting, but it does not fully replace data analysts. Data analysts, including those in roles like Student Shadow Data Analytics, are needed to interpret complex data, develop insights, and make strategic decisions that require human judgment and domain knowledge. Skills in data visualization, statistical analysis, and tools like Python or R remain essential for these roles.

What are the key skills and qualifications needed to thrive as a Student Shadow in Data Analytics, and why are they important?

To thrive as a Student Shadow in Data Analytics, you should have a foundational understanding of statistics, data interpretation, and basic programming, often gained through coursework or related academic projects. Familiarity with tools such as Microsoft Excel, SQL, and introductory data visualization software (like Tableau or Power BI) is typically expected. Eagerness to learn, attention to detail, and strong communication skills help you stand out in this observational and learning-focused role. These skills are crucial because they enable you to quickly absorb complex concepts, contribute to discussions, and make the most of your shadowing experience in a real-world data analytics environment.

Is 40 too late for data science?

The Student Shadow Data Analytics role involves learning data analysis skills, which can be pursued at any age. Many professionals successfully transition into data science later in life by gaining relevant skills such as programming, statistics, and tools like Python or SQL, regardless of age.

Does job shadowing mean you got the job?

Job shadowing, such as in a Student Shadow Data Analytics role, is an observational experience that provides insight into the work environment and tasks but does not guarantee employment. It is a learning opportunity and does not imply that a job offer has been made or received.
What are popular job titles related to Student Shadow Data Analytics jobs in Reston, VA? For Student Shadow Data Analytics jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Student Shadow Data Analytics jobs in Reston, VA look for? The top searched job categories for Student Shadow Data Analytics jobs in Reston, VA are:
What cities near Reston, VA are hiring for Student Shadow Data Analytics jobs? Cities near Reston, VA with the most Student Shadow Data Analytics job openings:
Student Shadow Data Analytics jobs near you

Data Analytics Engineer

Shadow Objects

Washington, DC • Remote

$129K - $155K/yr

Full-time

Posted 7 days ago

Job description

Job Title: Data Analytics Engineer
Clearance Requirement: Active DoD Secret Clearance required
Location: Remote / Pentagon

Position Overview

The Data Analytics Engineer is a hybrid role combining Data Analyst, Data Engineer, and Data Scientist responsibilities. This position operates with a high level of autonomy, owning projects end-to-end across functional areas. The ideal candidate is proactive, solution-oriented, and capable of identifying opportunities, reducing complexity, and delivering efficient, high-quality data solutions.

This role also provides guidance to team members, helps remove roadblocks, and contributes to the continuous improvement of processes, systems, and deliverables.

Key Responsibilities

Data Analysis & Insights

  • Gather, clean, and analyze complex datasets using advanced analytical techniques
  • Apply statistical methods to identify trends, patterns, and anomalies
  • Conduct exploratory data analysis (EDA) to support decision-making
  • Translate data findings into actionable insights for technical and non-technical stakeholders

Data Engineering & Pipeline Development

  • Design, develop, and maintain ETL/ELT pipelines using Databricks and Delta Lake
  • Implement Medallion Architecture (Bronze, Silver, Gold) to ensure data quality and scalability
  • Manage data ingestion processes with a focus on traceability and governance (e.g., Collibra)
  • Build and maintain data pipelines within DoD environments such as Advana/Jupiter
  • Troubleshoot, debug, and optimize data pipelines, identifying root causes and implementing solutions

Data Visualization & Reporting

  • Develop dashboards, reports, and visualizations using tools such as Tableau, Power BI, Qlik, or Foundry
  • Create interactive dashboards and reports to support operational and strategic decisions
  • Ensure accuracy, quality, and usability of all data visualizations and deliverables

Integration & System Support

  • Collaborate with data engineers, analysts, scientists, and stakeholders to deliver integrated data solutions
  • Support real-time data streaming using Databricks Structured Streaming
  • Optimize data storage solutions leveraging Delta Lake capabilities (e.g., schema evolution, time travel)

Governance & Compliance

  • Maintain data lineage and governance using tools such as Collibra
  • Ensure compliance with data security, privacy, and DoD requirements
  • Establish and enforce data quality standards across multiple data sources

Collaboration & Communication

  • Work closely with cross-functional teams to gather and refine requirements
  • Communicate findings, recommendations, and metrics clearly and professionally
  • Track assigned tasks and provide regular updates to leadership
  • Mentor junior team members and support team development initiatives
Required Qualifications
  • Active DoD Secret Clearance
  • Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field
  • 5+ years of experience in data engineering and building data pipelines and architectures
  • 5+ years of experience in data analysis, data mining, or business intelligence
  • 3+ years of experience developing data solutions using Python, SQL, and/or PySpark in big data environments (e.g., Databricks, Snowflake)
  • Strong experience with data visualization tools (Tableau, Power BI, Qlik, Foundry) and advanced Excel (macros, pivot tables, VBA)
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud
  • Familiarity with big data frameworks (Hadoop, Spark, Kafka)
  • Strong understanding of ETL processes, data warehousing, and BI best practices
  • Proven ability to analyze large datasets and communicate insights effectively
  • Strong problem-solving skills and attention to detail
  • U.S. work authorization required
Preferred Qualifications
  • Master’s degree in Data Engineering, Computer Science, or related field
  • Experience with DoD data platforms such as Advana and Jupiter
  • Familiarity with statistical methods (e.g., hypothesis testing, regression analysis)
  • Experience with SAP, Foundry, or advanced analytics platforms
  • Experience with NoSQL databases (e.g., Cassandra, MongoDB)
  • Knowledge of containerization tools (Docker, Kubernetes)
  • Experience with version control systems (Git) and Agile methodologies (Scrum, Kanban)
  • Prior experience in a client-facing government environment
Equal Employment Opportunity Statement

ShadowObjects, LLC is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.

Apply