So you decided to pursue a data analyst career path and are curious about what your career may look like in a few years?

Or, maybe, you're still deciding if a data analyst career path is the right track for you.

Either way, we've got you covered! In this article, we'll be sharing:

1. Data Analyst Careers To Pursue
2. The Data Analyst Career Path: Roles, Skills, & Progression
3. Data Analyst Salaries (Entry-Level, Mid-Level, & Senior Level)
4. Level-Up Your Game: How To Step Into A New Data Analyst Role

Data Analyst Careers To Pursue

There are several different career opportunities you can explore in the data analytics field. However, different industries might require more expertise in specific areas.

For example:

• A data analyst role at a tech startup might focus heavily on data visualization, performance metrics, and predictive analytics to provide actionable insights for business growth.
• A data analyst role at a healthcare company could emphasize data compliance, patient data management, and statistical analysis to optimize healthcare processes and outcomes.
• A data analyst role at a finance firm could offer opportunities in risk analysis, financial modeling, and investment forecasting to inform key decision-making.

Not all companies will demand every specialty, but every specialty has a place within many different companies!

So, if you're thinking about which data analyst career you should pursue, it might be a good idea to first consider what kind of company you would like to work for.

Maybe you'd like to work for a company in big tech.

Maybe you're aiming for a recognized brand in healthcare.

Or, maybe, you'd like to join a startup.

You will find different data analytics opportunities with different scopes and setups. Having clarity about where you'd like to be within a certain time frame is key to deciding which path is right for you.

Most skills you need for a data analytics career are transferable across different roles, industries, and companies. The purpose of the exercise is so you can look at the opportunities on your horizon and decide where you'd like to be in the short term and eventually down the road!

💡 Pro Tip:

If you're struggling to find out where you'd like to be, check out the article “What Should I Do With My Life? A Step-By-Step Guide” and read it from top to bottom. If “data analytics” still feels like the right path, head back here and continue reading!

Once you've set your mind on your career path, it's time to understand what roles might be a good fit for you.

The Data Analyst Career Path: Roles, Skills, & Progression

We've selected the most common data analyst roles for each level and their job descriptions. Take a look below!

Entry-Level Data Analyst Roles

Most people begin their data analyst careers in specialist roles, such as:

Data Analyst

This role offers broad exposure to different data analysis activities and doesn't usually require extensive experience.

📝 Data Analyst Job Description: Responsible for collecting, processing, and performing statistical analyses on large datasets to generate insights and recommendations for decision-making.

✅ Skills Required: Proficiency in Excel, SQL, and data visualization tools like Tableau or Power BI are key skills companies look for in Data Analysts.

⬆️ Possible progression: Data Analysts can progress into a Senior Data Analyst role.

Junior Data Scientist

This role requires a basic understanding of data science principles, including machine learning and statistical modeling.

📝 Junior Data Scientist Job Description: Responsible for working with structured and unstructured data, applying algorithms and statistical techniques to derive insights from the data.

✅ Requirements: Proficiency in Python or R, familiarity with machine learning libraries, and strong analytical thinking are the most required skills for this role.

⬆️ Possible progression: Junior Data Scientists can progress into a Data Scientist or Machine Learning Engineer role.

Business Intelligence Analyst

This role generally requires proficiency in BI tools and the ability to translate data into actionable insights but doesn't typically require extensive experience.

📝 Business Intelligence Analyst Job Description: Responsible for designing and creating data reports and dashboards that help businesses track key performance indicators and make data-driven decisions.

✅ Requirements: Proficiency in SQL, experience with BI tools like Power BI or Tableau, and strong communication skills are the most required skills for this role.

⬆️ Possible progression: Business Intelligence Analysts can progress into a Business Intelligence Manager role.

Mid-Level Data Analyst Roles

As you gain experience, mid-level roles often involve more responsibility and the opportunity to lead projects or teams. Some common mid-level data analyst roles include:

Senior Data Analyst

At this level, professionals are responsible for overseeing complex data analysis projects, guiding junior analysts, and communicating key insights to stakeholders.

📝 Senior Data Analyst Job Description: Responsible for leading data analysis initiatives, interpreting data trends, and providing recommendations based on data findings to support strategic decisions.

✅ Skills Required: Advanced SQL and Excel skills, proficiency in Python or R, data visualization expertise, and strong communication abilities.

⬆️ Possible progression: Senior Data Analysts can advance to roles like Data Analytics Manager.

Data Scientist

This role focuses on the application of statistical methods and algorithms to solve business problems, requiring deeper knowledge of data science and machine learning than entry-level roles.

📝 Data Scientist Job Description: Responsible for developing machine learning models, analyzing large datasets, and providing data-driven solutions to complex business problems.

✅ Skills Required: Strong programming skills (Python, R), machine learning, statistical analysis, and experience with big data tools like Hadoop or Spark.

⬆️ Possible progression: Data Scientists can move into positions such as Senior Data Scientist or Lead Data Scientist.

Business Intelligence Manager

This role is more specialized than entry-level roles and requires the ability to oversee the entire BI process, from data collection to reporting.

📝 Business Intelligence Manager Job Description: Responsible for managing BI teams, developing data strategies, and ensuring that business intelligence tools are optimized to provide actionable insights.

✅ Skills Required: Proficiency in BI tools, leadership, project management, and strategic thinking.

⬆️ Possible progression: Business Intelligence Managers can progress to roles like Head of Business Intelligence.

Senior-Level Data Analyst Roles

Senior-level roles involve greater strategic oversight and leadership, often requiring professionals to guide larger teams and make high-level decisions.

Data Analytics Manager

Data Analytics Managers are responsible for shaping the overall data strategy and ensuring that all data analysis efforts align with the company's objectives.

📝 Data Analytics Manager Job Description: Responsible for leading the data analytics team, overseeing complex data projects, managing large datasets, and ensuring the delivery of actionable insights to stakeholders.

✅ Skills Required: Leadership, project management, data strategy, and strong communication skills.

⬆️ Possible progression: Data Analytics Managers can move up to roles such as Director of Data Analytics.

Lead Data Scientist

This role requires deep expertise in data science and is responsible for leading the development and implementation of advanced data models and algorithms.

📝 Lead Data Scientist Job Description: Responsible for guiding the data science team in the creation of machine learning models, identifying trends in data, and providing high-level insights to support strategic business decisions.

✅ Skills Required: Advanced knowledge of machine learning, programming (Python, R), leadership, and strong analytical skills.

⬆️ Possible progression: Lead Data Scientists can advance to roles like Head of Data Science or Director of Data Science.

Director of Business Intelligence

This role oversees the entire business intelligence strategy for an organization and manages a team of BI professionals.

📝 Director of Business Intelligence Job Description: Responsible for developing and executing the BI strategy, managing large data sets, overseeing the creation of dashboards and reports, and ensuring the BI tools are optimized for decision-making processes.

✅ Skills Required: Leadership, strategic thinking, proficiency in BI tools, and strong project management skills.

⬆️ Possible progression: Directors of Business Intelligence can move up to executive roles such as Chief Data Officer (CDO).

Data Analyst Salaries (Entry-Level, Mid-Level, & Senior Level)

Now that we’ve covered the most common data analyst career paths, you might be asking yourself what the pay range is for each role.

To answer this question, let’s head over to one of our favorite tools for salary research: Glassdoor.

Glassdoor is one of the world’s top job and recruiting websites, where users can anonymously provide information about their companies – including their current salary. Glassdoor provides an average salary range for various roles based on the information sent by its users.

According to Glassdoor, the base salary for the most common data analyst roles in 2024 are:

Data Analyst Roles:

• Data Analyst (Entry-Level): $69K – $103K  / year base pay
• Senior Data Analyst (Mid-Level): $102K – $138K / year base pay
• Data Analytics Manager (Senior-Level): $120K – $170K / year base pay

Data Science Roles:

• Junior Data Scientist (Entry-Level): $77K – $144K / year base pay
• Data Scientist (Mid-Level): $92K – $142K / year base pay
• Lead Data Scientist (Senior-Level): $137K – $190K / year base pay

Business Intelligence Roles:

• Business Intelligence Analyst (Entry-Level): $79K – $127K / year base pay
• Business Intelligence Manager (Mid-Level): $122K – $161K / year base pay
• Director of Business Intelligence (Senior-Level): $135K – $204K / year base pay

Level-Up Your Game: How To Step Into A New Data Analyst Role

Whether you're looking for an entry-level job in data analysis or aiming to advance in your data analytics career, it's important to know that you don't necessarily need a graduate degree or specialization to move up the data analytics career ladder. Your unique experience and skills can go a long way, as long as you learn how to sell them!

Here are a few tips and tricks that will help you land your next data analyst role.

1. Run A Resume Scan To Find Out Skill Gaps In Your Target Role

Wondering if you are the right fit for that target role you've been eyeing?

We've got you covered.

Here's a simple, step-by-step guide to find out if you have the skills to land a job in data analytics you've:

1. Copy the job description of the data analyst role that sparked your interest
2. Head over to ResyMatch.io (or use our shortcut below)
3. Grab a copy of your most updated resume
4. Upload your resume on the left side
5. Paste the job description on the right side
6. Hit “Start Resume Scan”

Boom! ResyMatch will compare and score your resume against the job's description and identify missing skill gaps, such as:

ResyMatch will also make sure your resume is ATS compatible (ATS is a software that recruiters often use to track candidates through the hiring process). And of course, ResyMatch will provide suggestions and outline best practices you can use to edit and improve your resume!

Use our shortcut below to get started:

Step 1

Copy/paste or upload your resume here:

Click here to paste text

or

Upload a PDF, Word Doc, or TXT File

UPLOAD RESUME

Step 2

Paste the job post's details here:

Job Title Industry

Job Description

Step 3

Scan to compare and score your resume vs the job's description.

START RESUME SCAN

Or see a sample resume scan

Scanning...

2. Update Your Resume With Compelling Resume Bullets

After you've compared your resume against your target job description, you will likely find yourself in one of two scenarios:

1. You have some missing skills that you'll need to master before taking on a new role — if that's the case, you can take action and start building those skills through online courses and a portfolio strategy.

OR…

2. You have already mastered most of the skills — if that's the case, all you need to do is update your resume with compelling resume bullets, leveraging the keywords found in your resume and job description scan.

To get started, you'll want your resume bullets to have just the right amount of hard and soft skills, action words, measurable results, and common words. 

This means a compelling resume bullet for someone applying for a data analyst role might look something like this:

Improved data reporting accuracy by 25% through automating data validation processes, leading to a 15% increase in operational efficiency.

This bullet focuses on hard and soft skills specific to data analytics, while also showcasing measurable results!

To help you write the perfect resume bullet, we've created ResyBullet.io, a free resume bullet analyzer that helps you write your resume in a way that grabs attention and illustrates value. Simply copy and paste your resume bullet below to begin your analysis:

Free Resume Bullet Analyzer

Learn to write crazy effective resume bullets that grab attention, illustrate value, and actually get results.

Copy and paste your resume bullet to begin analysis:

Click To Analyze!

ResyBullet will analyze and score your resume bullet and give you actionable insights for improvement.

Here's how our resume bullet scored on ResyBullet:

If you're a visual learner, check out our video that walks you through the step-by-step of writing a crazy-effective resume bullet:

3. Build A Visually Appealing, ATS-Friendly Resume

Now that you've updated the content on your resume, it's time to transfer it over to an awesome layout that's also ATS-friendly.

We recommend using a resume template so you can save the time you'd normally spend designing your resume and instead allocate it to your job search.

You can use ResyBuild.io, a free AI resume builder, to easily build and customize your resume in no time. Just pick one of the templates below and get started:

Free Job-Winning Resume Templates, Build Yours In No Time.

Choose a resume template below to get started:

Choose from 8 proven templates and easily create, edit, and customize your resume. ResyBuild's AI assistant also helps you craft personalized, job-winning bullets in a single click. Simply add your experience, hit “Optimize,” and watch the magic happen.

4. Don't Apply Online — Do This Instead

The most common next step in the process is to start applying for data analyst roles.

While applying online can absolutely be the next step in your job search, the truth is, it will only get you so far. In fact, only 2% of resumes submitted for the average open role end up reaching the interview stage.

Sure, optimizing your resume will boost your chances of being a part of that 2%.

But some estimates, like this one from the Wall Street Journal, show that 80% of hires come from referrals.

This means your best shot at landing the role you've been eying is through networking.

And no, we're not talking about attending conferences, events, and meetups. We're talking about a fresh approach that really builds relationships and gets your resume at the top of the resume pile at companies like Microsoft, Google, Uber, and more.

You can read all about it in our flagship guide for effective job searching:

Read More: How To Get A Job Anywhere Without Applying Online

Final Notes

Whether you're just starting out or looking to advance in your data analyst career, getting clarity on the possibilities ahead of you can help you navigate your career with more ease.

Just don't forget: your career path isn't set in stone. Jobs and career goals will often evolve with life transitions. Always remember that your career should adapt to fit your life and not the other way around.