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Entry Level Analytics Engineer Jobs in Virginia (NOW HIRING)

MANTECH

Associate BI Analytics Engineer

Herndon, VA

As an entry-level position, you will work closely with senior engineers and stakeholders to deliver high-quality analytical solutions while growing your skills in business intelligence, data modeling ...

New

Augur Consulting

Entry-Level Analyst

Arlington, VA · On-site

Data Analytics & Visualization responsibilities include: Using PowerBI, Tableau, R, JACS, PO$T, CO ... Experience with MS Project, analytical software tools, and programing languages such as R, Python ...

Dewberry

Entry Level Site/Civil Engineer

Leesburg, VA · On-site

$82K - $85K/yr

Dewberry is seeking an Entry Level Site/Civil Engineer to join our Leesburg, VA office to work on ... Individual may analyze hydrologic and hydraulic models and computations for storm water and ...

Dewberry

Entry Level Site/Civil Engineer

Leesburg, VA

$82K - $85K/yr

Dewberry is seeking an Entry Level Site/Civil Engineer to join our Leesburg, VA office to work on ... Individual may analyze hydrologic and hydraulic models and computations for storm water and ...

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Entry Level Analytics Engineer information

What does an entry level analytics engineer do?

An Entry Level Analytics Engineer is responsible for building and maintaining data pipelines, transforming raw data into usable formats, and ensuring data quality for analysis. They work closely with data analysts and data scientists to create data models and automate data workflows, often using tools like SQL, Python, and cloud data platforms. Entry level positions focus on learning best practices, supporting senior engineers, and helping the organization make data-driven decisions by providing clean and reliable data.

What types of projects do entry level analytics engineers typically work on, and how do they collaborate with data teams?

Entry Level Analytics Engineers often assist with building and maintaining data pipelines, transforming raw data into usable formats for analysis, and developing reports or dashboards for business stakeholders. They work closely with data analysts to understand reporting needs and with data engineers to ensure data quality and efficient data flow. Collaboration is key, as they may participate in team meetings, code reviews, and documentation efforts to support broader analytics goals. This role provides hands-on experience with modern data tools while offering opportunities to learn from more senior team members.

What are the key skills and qualifications needed to thrive as an entry level analytics engineer, and why are they important?

To thrive as an Entry Level Analytics Engineer, you need a solid grounding in data analysis, SQL, and basic programming skills, often supported by a degree in computer science, statistics, or a related field. Familiarity with data modeling tools, analytics platforms like dbt, and cloud data warehouses such as Snowflake or BigQuery is typically expected. Strong problem-solving abilities, attention to detail, and effective communication are important soft skills that help bridge technical and business needs. These skills ensure accurate, actionable data insights and smooth collaboration with cross-functional teams in data-driven environments.

What is the difference between Entry Level Analytics Engineer vs Data Analyst?

AspectEntry Level Analytics EngineerData Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; some certificationsBachelor's in Statistics, Math, or related field; certifications optional
Work EnvironmentTechnical teams, data engineering projects, software toolsBusiness units, reporting, data visualization tools
Employer & Industry UsageTech companies, startups, data-driven organizationsFinance, marketing, healthcare, retail
Common Search & ComparisonYesYes

The Entry Level Analytics Engineer focuses on building data pipelines, integrating data sources, and supporting data infrastructure, often requiring programming skills. Data Analysts primarily interpret data, create reports, and visualize insights for business decisions. While both roles work with data, Analytics Engineers are more technical and infrastructure-oriented, whereas Data Analysts focus on analysis and reporting.

What are the most commonly searched types of Analytics Engineer jobs in Virginia?

The most popular types of Analytics Engineer jobs in Virginia are:

What are popular job titles related to Entry Level Analytics Engineer jobs in Virginia?

For Entry Level Analytics Engineer jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Entry Level Analytics Engineer jobs in Virginia look for?

The top searched job categories for Entry Level Analytics Engineer jobs in Virginia are:

What cities in Virginia are hiring for Entry Level Analytics Engineer jobs?

Cities in Virginia with the most Entry Level Analytics Engineer job openings:

Entry Level Analytics Engineer jobs near you
Infographic showing various Entry Level Analytics Engineer job openings in Virginia as of August 2026, with employment types broken down into 91% Full Time, 4% Part Time, and 5% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Associate BI Analytics Engineer

MANTECH

Herndon, VA

Full-time

Posted 3 days ago

New

ManTech rating

9.0

Company rating: 9.0 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

33rd of 244 rated software companies

Job description

hackajob is collaborating with MANTECH to connect them with exceptional professionals for this role.

MANTECH seeks an enthusiastic, detail-oriented Associate BI Analytics Engineer to join our Enterprise Data Analytics team in Herndon, VA. This is a hybrid position, requiring on site presence at least 2 days a week.

This role supports the build and maintenance of the data foundation that drives strategic decision-making across the enterprise. As an entry-level position, you will work closely with senior engineers and stakeholders to deliver high-quality analytical solutions while growing your skills in business intelligence, data modeling, and modern data engineering pipelines.

Responsibilities to include but not limited to:

  • Create, customize, and maintain visually compelling, intuitive, and high-performing Power BI dashboards and reports for internal stakeholders.

  • Assist in building and optimizing robust semantic models within Power BI using Star Schema design principles and basic DAX.

  • Support the team in maintaining, monitoring, and troubleshooting automated data engineering pipelines to ensure data accuracy and availability.

  • Validate data continuity and accuracy between source systems and reporting layers.

  • Work with business analysts and end-users to understand reporting requirements and document data definitions.

  • Collaborate with team members to translate technical data concepts into clear insights for non-technical stakeholders.

  • Participate in mentorship opportunities and continuously improve technical workflows within the team.

Minimum Qualifications:

  • High School Diploma/GED with 3+ years of experience, or a bachelor’s degree in computer science, Data Analytics, Information Systems, Mathematics, Economics, or a related field with 0-2 years of experience.

  • Experience creating reports, using Power Query, and understanding basic DAX functions within Power BI.

  • Solid understanding of relational databases and the ability to write clean SQL queries to extract and manipulate data.

  • Basic understanding of data warehousing concepts, dimensional modeling, and ETL/ELT processes.

  • Strong problem-solving skills with an analytical mindset and a keen eye for data trends or anomalies.

Preferred Qualifications:

  • Basic knowledge of Python or R for data analysis.

  • Exposure to cloud data platforms such as Microsoft Fabric or Databricks.

  • Familiarity with version control tools like Git.

  • Strong design sensibility regarding UI/UX layout, color theory, and data visualization best practices.

Clearance Requirements:

  • US Citizenship

Physical Requirements:

  • Must be able to remain in a stationary position 50% of the time.

  • Needs to occasionally move about inside the office to access file cabinets, office machinery, etc.

  • Frequently communicates with co-workers, management, and customers, which may involve delivering presentations. Must be able to exchange accurate information in these situations.

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