What Does An Entry-Level Data Analyst Do?

Considering a new career and want to know what an entry-level data analyst does? Check out this comprehensive guide!

Whether it’s due to pandemic-related job loss—or simply a desire to try something new—there are many people retraining for 21st-century jobs, with an especially popular one being data analytics. According to a survey by the executive recruiting firm Burtch Works, 81% of US data science and analytics teams are hiring new analysts during the second half of 2021, a trend that is being reflected worldwide.

This might sound great for your career-changing prospects, but before we get there, you might find yourself asking: what exactly is data analytics? Or maybe you’ll ask: what does an entry-level data analyst do? In this post, we’ll answer these pressing questions, and more:

  1. What is data analytics, and what does an entry-level data analyst do?
  2. How does a junior data analyst differ from a senior data analyst?
  3. What skills does an entry-level data analyst need?
  4. What is the average entry-level data analyst salary?
  5. Landing your first entry-level data analyst job
  6. How to get started as an entry-level data analyst
  7. Key takeaways and next steps

Ready to learn what a junior data analyst does and how to become one? Read on.

1. What is data analytics, and what does an entry-level data analyst do?

First up, let’s cover the basics.

What is data analytics?

In a nutshell, data analytics is the process of analyzing raw data to produce meaningful, actionable insights. This is possible because, well, data is everywhere! Every time someone clicks a link, buys something online, uploads a picture to Instagram, or orders an Uber, data is produced. Companies collect these data in vast repositories called data warehouses. By analyzing these data, companies can unleash their predictive power, vastly improving their competitive edge. 

Armed with data analytics insights—what customers are buying, what their travel habits are, what health issues they face—organizations are in a much better position to plan and make informed decisions about how to drive their strategies forward. It is this predictive power of data analytics—combined, of course, with the huge amounts of data that we now produce every day—that makes it such an in-demand role right now. And that’s data analytics in summary!

Learn more: What is data analytics? A complete guide for beginners

What does an entry-level data analyst do?

All data analysts share the same broad goal: uncovering the secrets hidden in big data. However, when you scratch beneath the surface, you’ll see that the role has many different aspects to it. As a junior data analyst, you won’t be expected to carry out business-critical tasks without oversight from someone more senior. While the role tends to become more specialized over time, we can make broad generalizations about what junior data analysts do.

Entry-level data analysts are usually part of a larger data analytics or data science team. Their role usually involves carrying out activities, which, taken together, are critical to the broader data analytics process. However, individually, these tasks are not necessarily high-stakes in themselves, allowing junior analysts to learn and hone their skills in a relatively safe environment, where any mistakes can be spotted and quickly corrected.  

As an entry-level data analyst, your job will commonly include: 

  • Collecting data: Usually from ‘safe’, or predetermined sources, before storing these data in a pre-existing data storage system, database, or warehouse.
  • Cleaning data: Part of the collection and storage process, you’ll be responsible for carrying out tasks like de-duping, standardization, and flagging missing values.
  • Producing reports: You’ll probably have to carry out basic data analyses and produce written reports of your findings, using tools like MS Excel or Power BI.
  • Helping create dashboards: You might be asked to help develop dashboards and visualizations to give non-technical personnel oversight of company data sources.
  • Databases: You’ll learn how to use in-house data storage systems, such as CRMs, ERP systems, and other databases.
  • Perfecting your wider skills: Entry-level data analysts must hone the skills that more senior analysts take for granted, from pattern recognition to problem-solving.
  • Weekly check-ins: Because you’re new, you’ll likely have weekly check-ins where you’ll have to explain what you’re working on to a more senior member of the team.

While the exact responsibilities vary, these broad tasks offer a taste of what you might expect during your first few weeks—or months—in a junior data analytics role. 

Entry level data analysts working together with graphs

2. What’s the difference between an entry-level or junior data analyst and a senior data analyst?

As we’ve seen, entry-level data analysts (also known as junior data analysts) carry out important—but not mission-critical—tasks. Their work is usually overseen by more senior counterparts, whose job is to take on the lion’s share of responsibility for the complex tasks.

While we can broadly define an entry-level data analyst as a graduate with up to three years of experience in the role, a senior-level data analyst (often referred to as a principal analyst or lead data analyst) requires more advanced skills.

Common distinguishing features of a senior analyst include:

  • Education: While an entry-level analyst role often requires a bachelor’s degree, a senior data analyst is likely to have a master’s (or even a Ph.D.) in a field such as computer science or statistics.
  • Programming skills: The vast majority of senior analysts are expected to be competent using programming languages such as Python or R at a high level.
  • SQL: Senior analysts will know how to create things such as temp tables and automated reports, and will generally be using more advanced code than entry-level analysts.
  • Analytics skills: In general, senior analysts will be carrying out analyses at a much higher level than junior ones, using much more sophisticated data models.
  • Management: Senior analysts are much more hands-on: leading projects, hiring staff, and establishing processes and performance metrics.
  • Mentoring: Except when they work alone, senior data analysts will be expected to mentor and oversee the work of their more junior counterparts.
  • Subject matter expertise: Senior analysts are essentially an organization’s go-to data experts—both for members of their team, as well as senior management and heads of departments. They can expect a lot of queries to come across their desk!
  • Advocacy: Senior analysts will often have to make the case for business decisions, promoting the benefits of data analytics and new technologies to the senior stakeholders who hold the purse strings.
  • Time in the role: All this additional expertise takes time to accrue. While some ambitious analysts may climb the ladder quickly, a senior data analyst role usually requires around 5 or more years of experience in more junior data analytics roles.

 As an entry-level data analyst, you won’t have to worry about these responsibilities, but that doesn’t mean you can’t use them as inspiration. Aim high—who knows where you might end up? 

3. What skills does an entry-level data analyst need?

Okay, so we know what skills a senior analyst needs but what about an entry-level data analyst? Rest assured that when you land that first job, you won’t be expected to know everything. Data analytics is a complex trade to perfect, and most employers understand this. As long as you can demonstrate the basic skills you need to hit the ground running, you’ll be in an excellent position to land that first role. 

Here are some basic requirements for landing your first entry-level data analyst job: 

  • Bachelor’s degree: While more senior analysts might have a master’s degree in something like computer science, at an entry-level role you’ll usually only require a bachelor’s. This can often be in a topic entirely unrelated to data analytics.
  • SQL: You’ll need to know what SQL is, but initially you’ll only need to know how to use it to query data in relational databases—nothing more complex than that!
  • MS Excel: You’ll need to be competent using spreadsheets, and understanding how to manipulate data using Excel’s basic analytics functions.
  • Python: Some basic coding is an inescapable part of data analytics. Python is the most commonly used language in the field, and luckily it’s fairly easy to learn!
  • Tableau: This data visualization software is fast becoming a data analytics staple. While not every company uses it, it may help to play around with the free version.
  • MS Power BI: Power BI is another powerful business intelligence platform. Thanks to Microsoft’s Office’s ubiquity, Power BI is a go-to tool for data analytics.
  • Presentation skills: On top of carrying out basic analytics tasks, you’ll have to present your findings to the wider team and other internal stakeholders.

 While these skills are the building blocks for any data analytics career, they may not be strictly necessary right away. For instance, if you’ve got solid Python skills, but don’t know how to use Power BI or Tableau, you can probably learn the latter on the job—or vice-versa. 

Likewise, if you lack a bachelor’s degree but instead have earned a well-regarded data analytics certification, there are many companies that view them equally. In short: stay passionate and keep an open mind. Always read the job description, and don’t worry if you don’t meet every single requirement they ask for, as skills can always be learned.

4. What is the average entry-level data analyst salary?

Data analytics is a bit of everything: it’s challenging, fascinating and, at times, yes, hard work! But that’s part of the joy of the job—no two days are ever the same, and the role can be highly satisfying. But let’s face it: we all have bills to pay. Which brings us to our next question: how much can you earn as an entry-level data analyst?

While there’s no foolproof answer, we can make an educated guess. As these salary comparison sites show, entry-level data analyst salary estimates can vary widely:

 To get a broad idea, an average of these salary estimates tells us that junior data analysts in the U.S. can expect to earn about $46,000 a year. Not bad, eh? While it’s probably safer to bet on this being a salary you can aim for within your first two or three years in general—rather than a baseline on your first day—data analytics pays pretty well.

Be sure to check out this data analyst salary guide for an idea of what you can earn as you progress up ranks into mid- and senior-level data analyst roles.

5. Landing your first entry-level data analyst job

In this section, we’ll explore everything you need to know to find and land your first data analytics job. First up, an obvious question:

What kinds of entry-level data analyst jobs are there?

Searching online, you may find job listings specifically seeking ‘entry-level data analysts’ or ‘junior data analysts’—but this won’t always be the case. More often than not, the level of experience required will be implied by the job responsibilities (as outlined in Section 3) and the years of experience the employer is expecting from you. As a rule of thumb, any job looking for up to three years of experience can usually be regarded as entry-level.

 Further complicating matters is the fact that job titles vary depending on the work being done. Here are some of the entry-level data job titles you might come across:

  • Marketing analyst
  • Customer analyst
  • Healthcare analyst
  • Clinical data analyst
  • Processing analyst
  • Data privacy and compliance analyst
  • Operations analyst
  • Business intelligence analyst
  • Sports analyst
  • Financial reporting analyst
  • Risk analyst

While these are just a few of the titles you might find, this list offers a taste of how broad the data analyst job market is. 

What industries can junior data analysts work in?

Before the dawn of the internet, data analytics was primarily used in the sciences—hardly surprising, given that science is so reliant on empirical data. However, with data now more or less freely available to anybody who wants it, many more industries are now adopting the scientific approach. The following industries are some of those in which competent data analysts are most sought after:

  • Finance
  • Accounting and insurance
  • Healthcare
  • Education
  • Advertising and marketing
  • Travel and tourism
  • Media and entertainment
  • Transport and logistics
  • Retail and ecommerce
  • The sciences

Each industry comes with nuanced skill requirements, which you can often learn on the job. However, if you’re transitioning from another career, your prior knowledge of that sector may benefit you if you choose to pursue data analytics in the same field.

What will you need to land your first data analytics job?

As well as the skills outlined in Section 1, there are a few practical things you’ll need to stand out to employers when applying for your first data analytics job, which include:

A certification evidencing your skills: Knowing your SQL from your Python and your qualitative data from your quantitative data is all good, but you’ll also likely need to prove that you know how to use them all, which usually requires some kind of data analytics qualification or certification. Fortunately, many affordable short courses can build your skillset and provide you with that all-important accreditation that employers demand—just be sure to check which courses employers will accept before splashing the cash!

A top-notch data analytics portfolio: While you won’t have a lot of experience yet, that doesn’t mean you can’t create a basic portfolio with some pet projects to show off your passion for the subject. You can gradually expand it over time. Most paid online courses culminate in a sample project— why not start by including that? Learn more about how to create your first data analytics portfolio.

A solid resumé and covering letter: When applying for any job, you’ll need a great data analyst resumé and covering letter. As an entry-level data analyst, employers won’t expect these to show a ton of experience, but they should be clear, well-written, and properly presented. Crucially, you must tailor them for each job you apply for. Nothing says lackluster like a generic resumé.

6. How to get started as an entry-level data analyst

Last, but not least: what’s the best way to get started as an entry-level data analyst? Here’s a brief overview of our guide to finding your first junior data analyst role.

Research some different industries you might want to work in: Have a look at the different industries currently employing data analysts and see which of them appeal to you most. This exercise isn’t about setting your career path in stone but simply narrowing your interests to keep you focused. Do you want to work in finance? Healthcare? Big tech? Knowing this will help you find suitable jobs later on.

Take a certified course: Once you’ve selected an industry of interest, check out what skills they call for, then find an online course that offers training in the right area. Regardless of industry focus, the most important thing is to find a quality course that provides you with the basic skills and ends with a qualification that employers recognize. Do your research before you fork out.

Polish up your portfolio: We’ve already mentioned the importance of a portfolio when applying for jobs in Section 5. For more inspiration, check out these 9 data analytics portfolio examples.

Start looking for jobs: At this point, you’re ready to look for real jobs! Check out common job sites like Indeed and Glassdoor, as well as data-specific job boards like Data Jobs. Of course, it’s also advisable to check out company careers pages to see if they are recruiting for any kind of data role.

Perfect your resumé and cover letter: Again, we touched on this in section 5, but having a tailored resumé and cover letter will help your application stand out from the others. It might feel like a lot of effort, but it’s worth it. It would be a shame to train the skills if you fall at this penultimate hurdle.

Apply, network, and keep at it! Finally, it’s time to start sending out those applications! Even if you don’t get a job right away, use the opportunity to network with potential employers. Don’t be disheartened if you don’t succeed right away. Just remember that data analysts are in demand, so the right job is out there for you somewhere!

7. Key takeaways and next steps

In this post, we’ve explored exactly what an entry-level data analyst does. We’ve learned that even junior data analysts require a baseline of skills—such as Python and MS Excel—as well as a broad understanding of the fundamentals of data analytics. However, we’ve also seen that entry-level data analysts won’t be expected to take on the degree of responsibility that falls to more senior analysts. Most likely, you will be carefully mentored in the role. 

Data analytics is challenging, well-paid (even at entry-level), and increasingly in-demand across almost every industry. With a qualification, basic skills under your belt, and a strong resumé and portfolio, you’ll be in a great position to land an entry-level data analytics job.  

Read more introductory topics with the following posts:

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