Your Guide to Entry Level Data Analyst Salaries

What can you expect to earn as a new data analyst in the U.S.? A typical starting salary lands between $65,000 and $95,000 per year.

Think of that range as your baseline. Your actual offer will depend on your skills, location, and the type of company you join. This guide will give you the practical steps to aim for the top of that range, especially if you are targeting remote jobs.

Understanding Your Starting Salary Potential

Landing your first data analyst role is a huge achievement. Knowing the salary landscape is your first step to getting a fair offer. The national average is a good starting point, but your final number will be shaped by your skills in tools like SQL and Tableau, the industry you target, and whether the job is remote or in a major tech hub.

The good news is the field is growing fast. As of early 2025, the average salary for new data analysts reached about $90,000, a significant increase from the $70,000 average just a year before. This points to a massive demand for professionals who can interpret data. In fact, the U.S. Bureau of Labor Statistics projects data science roles will grow by 23% through 2032, which you can read about in this data analyst job outlook report. For new graduates, that growth means more job opportunities and more room to negotiate.

Let's break down the key factors that can boost your starting pay.

As you can see, where you work and what you know makes a huge difference. An analyst in San Francisco working for a major tech firm will almost always start with a higher salary than someone in a smaller city working for a local nonprofit.

Key Factors Influencing Your First Salary

Before you negotiate, you need to understand the variables that impact your offer. Knowing what matters helps you set realistic goals and build leverage. If you are just starting out, getting prepared is half the battle; our guide on how to get your first job after college has practical tips.

Here are the main things that determine your starting pay:

• Location: Salaries in places with a high cost of living, like New York City or the Bay Area, are significantly higher. Remote jobs can change this dynamic.
• Company Size: Large tech companies and established corporations have bigger budgets and tend to offer more competitive starting salaries compared to startups.
• Industry: Your salary can look very different depending on the sector. Finance, tech, and healthcare typically pay more than industries like retail or the nonprofit sector.
• Skills & Certifications: This is where you have the most control. Demonstrating expertise in in demand tools like Python, Power BI, or a cloud platform like AWS can directly increase your offer.

Once you understand how these factors work together, you will be in a much stronger position to evaluate offers and confidently negotiate for the compensation you have earned.

How Location and Remote Work Shape Your Paycheck

Where you live, or choose not to live, is one of the biggest factors in your earning potential. It is well known that a data analyst salary in a major tech hub like San Francisco will be higher than in a smaller city. Companies must account for the large differences in living expenses.

The growth of remote work is changing this situation. It is beginning to separate salary from location, creating a huge opportunity to increase your income's buying power.

This chart gives you a quick visual on the year over year growth in what companies are willing to pay for new data talent.

The trend is clear: demand for data skills is pushing salaries up across the board.

Maximizing Your Income with Remote Roles

Let's consider a scenario. You land a remote data analyst job with a company based in New York City. They offer you a competitive starting salary of $95,000, which is standard for their high cost market.

Instead of living in a small apartment in Manhattan, you decide to work from a city with a much lower cost of living, like St. Louis, Missouri.

Suddenly, that $95,000 salary feels much larger. Your housing, transportation, and daily costs are just a fraction of what they would be in New York. This is the financial power of remote work: earning a top tier salary without top tier expenses. Our guide on how to land high paying data jobs from home explores these strategies in more detail.

The real advantage of targeting remote jobs is unlocking a higher quality of life. By separating your salary from your location, you can significantly boost your disposable income and financial freedom right from the start of your career.

As of 2025, the salary landscape reflects this shift. While typical entry level salaries fall between $65,000 and $85,000 a year, hubs like San Francisco and New York are pushing starting pay into the $102,000 to $118,000 range. Even more telling is that many remote roles are now breaking the $100,000 mark, offering a huge financial win without forcing you to relocate.

Companies are still determining how to handle compensation for a distributed workforce. Some adjust pay based on the employee's location, while others have adopted a single national rate. Understanding these models is critical when you are looking at remote offers. Jobsolv’s remote job board helps you target companies with favorable pay policies, giving you a strategic edge in finding a high paying entry level role.

The Skills That Command a Higher Starting Salary

Not all entry level data analyst roles are the same, and neither are the skills you bring. While a solid foundation in Excel and basic SQL will get you an interview, mastering a few high value skills is what convinces a company to offer you a salary at the top of their range.

Your ability to solve expensive business problems is directly tied to your earning potential. Think of it this way: a company might pay you to run weekly reports, but they will pay you more if you can automate that process and save the team five hours every week.

That is the difference between completing tasks and solving problems. Your goal is to showcase skills that deliver measurable business value from day one.

This is why proficiency in tools like Python or advanced SQL can increase your salary offer by 5% to 8%. These skills show employers that you can handle complex challenges efficiently.

Technical Skills That Boost Your Paycheck

To command a higher entry level data analyst salary, focus on building expertise in tools that solve high impact business problems. These are the skills that consistently appear in higher paying job descriptions for remote and hybrid roles.

Here are the key technical skills to master:

• Advanced SQL: Move beyond simple SELECT statements. Recruiters look for your ability to use window functions, common table expressions (CTEs), and complex joins to pull detailed insights from large databases. This shows you can handle sophisticated data retrieval tasks independently.

• Python for Automation: Knowing Python, particularly libraries like Pandas for data manipulation, is a major advantage. A simple script that cleans and merges datasets can save a company dozens of hours a month. Highlighting a project where you automated a report on your resume is a powerful way to demonstrate your value.

• Data Visualization Mastery: Expertise in tools like Tableau or Power BI is essential. You need to do more than build charts; you must create interactive dashboards that tell a compelling story. A manager should be able to look at your dashboard and immediately understand business performance without needing an explanation.

Certifications That Get You Noticed

Beyond your core technical skills, professional certifications act as a credible signal to hiring managers that your knowledge is current and verified. They are especially valuable when you have limited professional experience.

A relevant cloud certification can be the tiebreaker that lands you a higher salary offer. It proves you understand the modern data stack and can work with the tools that power today's data driven companies.

Consider pursuing one of these high value certifications:

• Cloud Platform Certifications: An AWS Certified Cloud Practitioner or Microsoft Certified: Azure Data Fundamentals certificate shows you understand cloud environments where most companies store their data.
• Tool Specific Certifications: Certifications from Tableau or Microsoft for Power BI validate your expertise in the exact tools listed in the job description.

Featuring these skills and certifications on your resume is critical. Jobsolv’s free ATS approved resume builder helps you strategically place these keywords, ensuring your application gets past automated screeners and into the hands of a recruiter.

Why Company Size and Industry Matter for Your Salary

Who you work for can be just as important as the skills you have. The size of a company and its industry are huge factors that shape your starting salary as a data analyst. A massive tech company with deep pockets has a different budget for new hires than a fast moving startup.

Similarly, an analyst role in the high stakes finance sector will almost always have a different pay scale than one in retail. Your choice of employer directly influences not just your paycheck, but also the kind of experience you will gain.

Big Tech vs. Startups

Large, established technology companies are known for offering some of the highest entry level salaries. They have the resources to attract top talent and often include generous benefits, stock options, and bonuses that seriously boost your total compensation. The work is often structured, and you will learn from established processes within large, experienced teams.

On the other hand, startups might offer a lower base salary but could provide equity that might become valuable later on. The real draw for many is the hands on experience. You will likely wear many hats, work on a ton of different projects, and see your impact more directly. This environment can be a fantastic learning ground for developing a broad skill set quickly.

Salary Benchmarks by Industry

The industry you choose plays a decisive role in your earning potential. It is no secret that the tech and finance industries consistently lead the pack for analyst compensation.

Your industry choice sets the stage for your long term career earnings. A role in a high growth sector like technology or finance not only offers a strong starting salary but also provides a pathway to more lucrative specialized roles down the line.

Labor statistics from 2025 show that the average entry level data analyst salary in the US is around $90,000, but this figure changes dramatically by sector. Major tech companies sit at the top end, with Meta offering new analysts an average of $123,000, Apple around $95,800, and Microsoft approximately $93,000. In contrast, a financial data analyst might start closer to $64,375, though specialized roles in this field can climb much higher with experience. You can read more about these salary negotiation insights.

Here is a quick look at how different environments stack up:

• Large Tech Companies (e.g., Meta, Microsoft): Highest base salaries, structured roles, and comprehensive benefits.
• Startups: Potentially lower base pay but offer valuable equity and broad, hands on experience.
• Finance & Banking: Strong salaries with high potential for bonuses, requiring specialized domain knowledge.
• Healthcare & Retail: Competitive but generally lower starting salaries compared to tech, with a focus on operational analytics.

Choosing the right fit means weighing your financial goals against your career development priorities. Jobsolv's job board helps you filter by industry, allowing you to target remote and hybrid roles in sectors that best match your salary expectations and long term ambitions.

How to Negotiate Your First Data Analyst Offer

Negotiation is not just for senior executives. It is a critical skill from your very first job offer, and getting it right sets the path for your future earnings.

It is easy to feel intimidated, but most companies expect you to negotiate. They often build some flexibility into their initial offer. Your job is not to be pushy; it is to confidently show them what you are worth based on the market.

With preparation, you can turn a potentially awkward conversation into a professional discussion that lands you the salary you deserve.

Do Your Homework Before the Conversation

The most critical part of negotiation happens before you ever speak to the hiring manager. You must enter that conversation armed with data. Start researching the typical data analyst salary entry level benchmarks for your specific city, industry, and the company's size.

Lean on credible sources to build your case. Sites like Glassdoor, LinkedIn Salary, and Levels.fyi are excellent resources for this information. Your goal is to find at least three solid data points that support the salary range you are targeting. This step reframes the conversation from "what I want" to "what the market dictates."

Remember, the goal of salary negotiation is to reach a mutually agreeable number. By grounding your request in market data, you transform the conversation from a personal plea into a professional business discussion about fair compensation for your skills.

Frame Your Value and Make the Ask

Once you have your target salary backed by research, the next step is to connect that number to the specific value you will bring to their company. They are not just hiring a generic data analyst; they are hiring you to solve their unique problems.

This is your chance to tie your skills directly to the job description. Instead of saying "I would like more money," frame your request around the impact you will make.

Here is how that might sound:

• Focus on high impact skills: "Based on my research for similar roles in the tech industry here in Austin, and my proficiency with Python for automating reports, a salary between $X and $Y would be more in line with the value I can bring to this position."
• Connect to their specific needs: "I am very excited about the opportunity to build interactive Tableau dashboards for the marketing team. Given my experience with data visualization and the current market rates for that skill set, I was hoping we could discuss a starting salary closer to $Z."

Throughout the conversation, stay positive and enthusiastic about the role. The key is to be collaborative, not confrontational. When you state your case clearly and confidently, you are not just asking for more money. You are showing the employer that you know your worth and are ready to deliver from day one.

Build a Resume That Unlocks a Higher Salary

Your resume is the single most important tool you have for unlocking a higher data analyst salary entry level. Before you can negotiate an offer, you have to get noticed. That means building a resume that impresses both the Applicant Tracking System (ATS) and the hiring manager.

This is where many job seekers make a mistake. They list past duties. A vague statement like "analyzed sales data" is forgettable and does nothing to sell your skills. It is a guaranteed way to be overlooked.

Speak in Numbers, Not Just Words

To stand out, you need to translate your work into measurable business results. Think from the hiring manager’s perspective: how did your projects help the company? Did you save time? Cut costs? Improve a process?

Let’s look at two before and after examples.

• Before: Created reports using Python.

• After: Reduced data processing time by 20% by developing automated Python scripts to clean and merge large datasets.

• Before: Built dashboards in Tableau.

• After: Designed an interactive Tableau dashboard that delivered daily sales insights, leading to a 10% increase in forecast accuracy.

The difference is clear. This approach does not just say what you did; it proves you can deliver tangible value. For more ideas on how to frame your achievements, check out these entry level data analyst resume examples.

Think of your resume as a marketing document, not a history lesson. Every single bullet point should answer one question: "How did I make things better?"

To get past the initial ATS screen, you also need to use the right keywords. Strategically include high value keywords from the job description, like SQL, Tableau, Power BI, and remote work. This ensures your resume aligns with what recruiters are searching for.

Jobsolv’s free ATS approved resume builder and tailoring tools are designed for this. They help you craft targeted applications that put your most valuable, quantified achievements front and center. This positions you perfectly for higher paying remote and hybrid jobs.

Answering Your Top Questions About Data Analyst Pay

Let's clarify a few common questions. When you are preparing to land your first role, knowing what is realistic and what is possible is key.

Can a Data Analyst Really Make $100k?

Yes, absolutely. Hitting six figures as a data analyst is achievable, even for someone relatively new to the field.

A $100,000+ salary is not the standard for a brand new analyst, but it is far from impossible. You can reach this level by being strategic: targeting high paying sectors like tech or finance, pursuing remote roles based in high cost cities, or mastering in demand skills like Python and cloud platforms.

Is Being a Data Analyst a High Stress Job?

This depends more on the company culture than the role itself. If an organization values hitting deadlines over personal time, any job there will feel stressful.

However, most data professionals find their work very satisfying. The job is about solving puzzles and uncovering insights, which is incredibly engaging. Landing a remote or hybrid position can also make a significant difference in your work life balance.

Do I Need a Degree to Get Hired as a Data Analyst?

No, a four year degree is not the only path to becoming a data analyst. While many analysts have degrees in math, statistics, or computer science, companies are shifting their focus from credentials to capabilities.

A strong portfolio that showcases real projects, along with key certifications, can be just as convincing as a diploma. It proves you can deliver actual results, which is what hiring managers truly care about.

Ready to find a remote role that pays what you're worth? Jobsolv’s free ATS approved resume builder and remote job board help you target high paying data analyst positions. Get started on Jobsolv today and land the job you deserve.