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Entry Level Analytics Engineer Jobs (NOW HIRING)

Allegion

Associate Analytics Engineer

Carmel, IN · On-site

Associate Analytics Engineer This position functions within Allegion's Global Data & Analytics Team ... This role is an entry-level or early-career position to support how the business and other IT teams ...

Allegion

Associate Analytics Engineer

Carmel, IN

Associate Analytics Engineer This position functions within Allegion's Global Data & Analytics Team ... This role is an entry-level or early-career position to support how the business and other IT teams ...

Symetra

Analytics Engineer, AI Enablement (Remote)

$96K - $161K/yr

About the role As an Analytics Engineer, you'll help build the data platform our AI products run on ... I started in an entry-level position and have worked my way up to Unit Manager by continuously ...

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 ...

Reliance One

Entry-Level Engineer

Toledo, OH

$27.58/hr

Entry-Level Product Quality Engineer Toledo, Ohio, United States $27.58 per hour Contract ... cause analysis, and continuous improvement. Key Responsibilities • Investigate and resolve ...

Tecolote Research

Entry Level Analyst

Washington, DC · On-site

$55K - $75K/yr

Responsibilities Data Analytics * Analyze monthly Integrated Program Management Reports, including ... Integrate information from program management, scheduling, finance, engineering, and risk ...

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All JobsAnalytics Engineer JobsEntry Level Analytics Engineer Jobs

Entry Level Analytics Engineer information

See salary details

$40.5K

$86.4K

$142.5K

How much do entry level analytics engineer jobs pay per year?

As of Jul 28, 2026, the average yearly pay for entry level analytics engineer in the United States is $86,381.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $103,500.00 per year, depending on experience, location, and employer.

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 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 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 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.
More about Entry Level Analytics Engineer jobs
What cities are hiring for Entry Level Analytics Engineer jobs? Cities with the most Entry Level Analytics Engineer job openings:
What are the most commonly searched types of Analytics Engineer jobs? The most popular types of Analytics Engineer jobs are:
What states have the most Entry Level Analytics Engineer jobs? States with the most job openings for Entry Level Analytics Engineer jobs include:
What job categories do people searching Entry Level Analytics Engineer jobs look for? The top searched job categories for Entry Level Analytics Engineer jobs are:
Entry Level Analytics Engineer jobs near you
Infographic showing various Entry Level Analytics Engineer job openings in the United States as of July 2026, with employment types broken down into 69% Full Time, 8% Part Time, and 23% Contract. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $86,381 per year, or $41.5 per hour.
Analytics Engineer I (Entry-Level) (3897)

Analytics Engineer I (Entry-Level) (3897)

Navarro Inc.

Oak Ridge, TN • On-site

Full-time

Posted 22 days ago

Job description

Navarro Research and Engineering is recruiting anAnalyticsEngineerI(Entry-Level)(3897)in Oak Ridge, TN.

Navarro Research & Engineering is an award-winning federal contractor dedicated to partnering with clients to advance clean energy and deliver effective solutions for complex challenges in the nuclear and environmental fields. Joining Navarro means being a part of an exceptional team committed to quality and safety while also looking for innovative strategies to create value for the client's success. Headquartered in Oak Ridge, Tennessee, Navarro has active programs in place across the nation for DOE/NNSA, NASA, and the Department of Defense.

Position Summary

The Analytics Engineer I (Entry-Level) will support Navarro's Data & Analytics team by helping build andmaintaindata pipelines,assistingwith reporting and dashboarding efforts, and contributing to applied AI projects. This role is well suited for an early-career professional interested in growing intoa strong analyticsor applied AI contributor, including work involving AI/ML techniques to extract, structure, andvalidatekey information from unstructured documents.

Responsibilities

  • Assistin designing, building, and maintaining data pipelines and ETL/ELT processes.
  • Write andoptimizeSQL queries to extract, transform, and analyze data from multiple sources.
  • Support the development of dashboards and reports using Excel and other business intelligence tools.
  • Use Python and/or R to automate data workflows, clean datasets, and perform exploratory analysis.
  • Build and support AI/ML-driven workflows for extracting key text and structured data from documents, including NLP, LLM-based extraction, and OCR plus ML pipelines.
  • Collaborate with data scientists, analysts, and business stakeholders to understand data and applied AI project needs.
  • Help document data models, pipeline logic, and AI/ML workflow processes.
  • Contribute todata quality checks and validation processes for both traditional data and AI-generated outputs.

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