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Entry Level Data Modeling Jobs (NOW HIRING)

Entry-Level Software Engineer Job Overview We are seeking an enthusiastic Software Engineer to join ... Proficiency with SQL and relational data modeling * Must be able to program without use of AI tools ...

This role is an entry-level position and is expected to perform assigned duties under established ... modeling. * Ability to retrieve and analyze data using SQL from sources such as SQL Server ...

This role is an entrylevel position and is expected to perform assigned duties under established ... modeling. * Ability to retrieve and analyze data using SQL from sources such as SQL Server ...

M365 Platform Developer

Suffolk, VA · On-site

$105K - $115K/yr

Responsibilities This entry-level data science role supports the development of analytical tools ... Perform analysis and modeling of large, complex data sets to identify patterns, trends, and ...

Responsibilities This entry-level data science role supports the development of analytical tools ... Perform analysis and modeling of large, complex data sets to identify patterns, trends, and ...

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Entry Level Data Modeling information

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How much do entry level data modeling jobs pay per hour?

As of Jun 29, 2026, the average hourly pay for entry level data modeling in the United States is $19.05, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $21.39 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Data Modeling vs Data Analyst?

AspectEntry Level Data ModelingData Analyst
Required CredentialsBachelor's in CS, IS, or related; basic understanding of databasesBachelor's in Statistics, Math, or related; proficiency in data tools
Work EnvironmentDesigning data structures, collaborating with DBAs and developersAnalyzing data sets, creating reports, working with business teams
Industry UsageUsed in database design, data warehousing, and system developmentApplied in business intelligence, reporting, and data-driven decision making

Entry Level Data Modeling focuses on designing and structuring data systems, while Data Analysts interpret data to provide insights. Both roles require foundational data knowledge but differ in their primary tasks and focus areas within the data ecosystem.

What are the key skills and qualifications needed to thrive as an Entry Level Data Modeler, and why are they important?

To thrive as an Entry Level Data Modeler, you need a solid understanding of database concepts, data structures, and basic SQL, often supported by a degree in computer science or a related field. Familiarity with data modeling tools such as ER/Studio, Microsoft Visio, or IBM InfoSphere Data Architect, and knowledge of relational database management systems (RDBMS) are typically required. Strong analytical thinking, attention to detail, and effective communication help you clarify requirements and present technical information to stakeholders. These skills and qualities ensure that data models are accurate, scalable, and aligned with business needs, supporting successful data-driven projects.

Can I work a data entry job with no experience?

Entry level data modeling roles typically require some familiarity with database concepts and basic data management tools, but many employers accept candidates with little to no experience if they demonstrate strong attention to detail and willingness to learn. Basic skills in Excel or similar software can be sufficient to start, and on-the-job training is often provided. Certifications in data management or related areas can improve prospects but are not always mandatory for entry-level positions.

Is 40 too late for data science?

Entry level data modeling roles typically require foundational skills in database design, SQL, and data analysis. Age is not a barrier; many professionals transition into data science or modeling careers later in life by acquiring relevant certifications and skills through online courses or bootcamps.

What is entry level data modeling?

Entry level data modeling involves creating and organizing data structures, such as diagrams and databases, to represent and manage information within an organization. Professionals in this role typically use tools to define how data is stored, accessed, and related, ensuring it supports business needs. Entry-level data modelers work closely with senior analysts and IT teams to learn best practices and standards. This position is ideal for those with foundational knowledge in databases, analytical thinking, and an interest in data-driven decision making.

How to start with data modelling?

Entry level data modeling involves understanding database concepts, learning data normalization, and practicing with tools like ER diagrams and SQL. Gaining familiarity with data management principles and obtaining certifications such as Microsoft Certified: Data Analyst can also help build foundational skills for this role.

Will AI replace data modelers?

AI tools can automate certain aspects of data modeling, such as generating schemas or identifying patterns, but data modelers are essential for designing complex data structures, understanding business needs, and ensuring data quality. Human expertise remains critical for interpreting requirements and making strategic decisions, especially in complex or evolving environments. Data modelers who develop skills in data governance and modeling tools will continue to be valuable in the job market.

How does an entry-level data modeler typically collaborate with other teams during a project?

As an entry-level data modeler, you will often work closely with business analysts, software engineers, and database administrators to translate business requirements into effective data structures. Collaboration often involves participating in meetings to gather requirements, reviewing data needs, and ensuring your models align with both business goals and technical constraints. You may also assist in refining models based on feedback and help maintain clear documentation for future reference. This teamwork not only improves your technical skills but also helps you understand the broader context of data-driven decision-making within the organization.
What are the most commonly searched types of Data Modeling jobs? The most popular types of Data Modeling jobs are:
What states have the most Entry Level Data Modeling jobs? States with the most job openings for Entry Level Data Modeling jobs include:
Data Scientist - Multiple Levels (TS/SCI with Poly Required)

Data Scientist - Multiple Levels (TS/SCI with Poly Required)

Red Alpha

Columbia, MD • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

A little about us:
The Red Alpha Data Science practice grew out of Red Alpha's reputation in Software and System Engineering with our Department of Defense clients. As sometimes happens, customers who trust our expertise in adjacent areas asked Red Alpha to assist with some of their burgeoning Data Science problems.

Culturally, it probably suffices to say that we take our work seriously, but not ourselves. Our leaders have spent time in the trenches and have cursed daylight savings time changes and trailing whitespace as many times as you have. We like to say that we spend 80% of our time cleaning the data...and 20% of our time complaining about cleaning the data. Joking aside, our voices matter, and it is easy to see how our decisions affect the Data Science practice and Red Alpha as a whole. We have a clear vision of where we are headed.     

Our team takes a pragmatic approach to Data Science, defining it loosely as the intersection of technical expertise, business acumen, and soft skills to solve business problems with data. We spend a lot of time trying to understand the problem before we set about building a solution, and we prefer lower tech useful solutions over shiny algorithms and dust on the shelf. Did we mention we’re pragmatic? We have a diverse set of skills across our team, and whether you are a traditional Data Scientist (whatever that means…), an Applied Research Mathematician, a Database Engineer, a Full Stack Developer, or something else in that neighborhood, if you have a knack for picking apart data to make sense of it, we would enjoy having a conversation with you.     

A day in the life:
You’ll likely start your day at a customer location near our Red Alpha offices, checking to see if there are any important items that have just come up. If not, you’ll move on to improving a dashboard or other data product that you’re responsible for, or perhaps produce a weekly output the customer is expecting. You’ll be using R or Python a lot, but also Git, Mongo, some commercial software and several other usual suspects. Once a week you’ll attend a team meeting (with 4 others) to prioritize things, and you’ll have a lot of interaction with the team otherwise, typically several times per day. You’ll need your sense of humor and need to be willing to leave your ego at the door.     
     
What you bring to the table:
Now on to the fun of formal requirements - we have to apologize in advance for the corporate-speak here, but just hold your breath for a few lines and everything will be okay. We are actively hiring data professionals for roles across a broad range of skill levels and projects. Our goal is to find the best fit for you so please note that if you apply to one of them and we see a fit elsewhere we will let you know. So do not worry about applying initially for every position you might be interested in.
All of our data scientists need the following skills:     
  • Proficiency with a scripting language such as R or Python
  • Experience with data science techniques and algorithms such as classification, clustering, random forests, deterministic forests (jk), hierarchical modeling, deep learning, Markov Chain Monte Carlo, and others. Note that you do not need to have all of these (we hope you enjoyed our random smattering of techniques…!) but you should be comfortable and capable with several of them and know some others not on this list.
  • A B.S. Degree in Data Science, Mathematics, Computer Science or related field.
  • For entry-level data scientists, 0-3 years of experience on Data Science projects.
  • For mid-level data scientists, 3-6 years of experience on Data Science projects.
  • For senior-level data scientists, at least 6 years of experience on Data Science projects with at least 3 years of experience managing teams.
  • A TS/SCI with Polygraph security clearance.
These are important skills to have, but not necessarily mandatory:     
  • Exceptional interpersonal skills. You know, as in you might not be at the top of the list to be a game show host but you do like people and enjoy solving problems jointly with your colleagues.
  • Experience with Java, C, or other compiled languages
  • Comprehensive knowledge of Saturday Night Live sketches (just kidding)
  • Experience with SQL/NoSQL, Spark, Hadoop
  • Familiarity with Javascript and Scripting
  • Familiarity with Docker, GitLab, and React

The total package:
 
Our total compensation package was strategically designed with our members in mind with the intention to: reward our members for their hard work and commitment to our customers' missions; allow members to share in Red Alpha's success as we continue to grow and expand our footprint; provide long-term career opportunities through stability and internal mobility; and provide the resources our members need to support themselves and their dependents in the form of a robust benefits package.  Our total compensation package includes a competitive base salary and benefits such as health, life/disability, 401k, paid time off, professional development, and generous bonus programs.  Please visit our benefits tab for additional information. 
 
Salary Range:   
  • Disclosed pay ranges are a general guideline, and are not a guarantee of a final salary or compensation.  Our approach in determining final salaries takes into consideration a number of factors such as education, certifications, total years of relevant professional experience, actual level of expertise, and the responsibilities of the role itself. 
  • Based on the outlined roles, responsibilities, and requirements, the  projected pay range for these positions are:
    • Entry-level:  $95,000 - $135,000
    • Mid-level: $110,000 - $155,000 
    • Senior-level:  $135,000 - $235,000
Some of our additional perks and benefits include:                 
  • Retire sooner than planned: Get closer to retirement with up to 10% in 401k contributions, immediately vested. 
  • Have a career AND a life: Enjoy up to 5 weeks of leave (25 days of personal time off) and 11 paid floating holidays.
  • Stay at your best: As a member, we'll pay 100% of your premiums for comprehensive health, dental, and vision insurance. We'll also pay the majority of the premiums for your family.  Let's not forge free access to a fully equipped state of the art gym!
  • Keep current on new technologies and technological advancements:  $5250 per year towards ongoing education, trainings, certifications, and maintaining professional memberships. 
  • Dress in style:  Spend up to $300 per year on company branded merchandise featuring top quality brands such as Under Armour, Nike, Carhartt, YETI, etc.
  • Enjoy the culture:  Attend fun company events throughout the year such as our Oktoberfest, summer picnic, and annual holiday party!  These are all in additon to your team events which may include happy hours, baseball games, snowboarding, RenFest, and more!
 
Every day, our elite customers are pushing through "the grind" to defeat the enemy, even putting their lives on the line for our freedom. Rise to the occasion with us to deliver engineering excellence, to match their dedication to this nation. Join us as we bring digital transformation to the fight!