Data Analyst Salary: 5 Pressing Questions Answered. What’s a typical data analyst salary? How much can those with a lot of experience and skills potentially earn?
Data analysts are crucial members of many organizations. Executives rely on data analysts’ work product to make vital decisions about the overall direction of the business. On a team level, data analysts also provide those valuable insights that allow developers, engineers, and others to make short-term decisions.
Data Analyst Salary: 5 Pressing Questions Answered
In other words, data analysts can mean the difference between success and failure. But does the average data analyst salary match the role’s actual importance to the organization? That’s a very big and complicated question.
Before we begin, it’s important to differentiate data analysts from data scientists and data engineers. Some people treat “data scientist” and “data analyst” as interchangeable terms, and the roles do have some overlap—for example, both utilize some of the same tools to deliver insights to their respective audiences. However, data analysts tend to focus on smaller-scale, more tactical problems, whereas data scientists are often deployed to tackle more strategic, longer-term challenges. (Data engineers are something totally different, meanwhile; they’re usually tasked with constructing and maintaining the data infrastructure that data analysts and data scientists rely on.)
With that in mind, let’s jump into our analysis of data analyst salary.
What is an average data analyst salary?
According to Burning Glass, which collects and analyzes job postings from across the country, the median data analyst salary is $78,676. As we’ll break down below, though, your level of education and experience can have a radical effect on how much you earn.
What are the most valuable skills for a data analyst?
A typical data analyst might end up using some combination of the following tools:
- Postgresql (an open-source relational database management system)
- RapidMiner (a data-science platform used by many companies)
- Knime (an analytics platform)
- Datawrapper (an online tool for creating charts and visualizations)
- Tableau (another visualization tool)
- SAS Sentiment Analysis
- Google Fusion Tables
- Apache Hadoop
Versatile data analysts will also know their way around R and Python, two programming languages that are driving data-analysis coding at the moment (keep in mind that R is definitely more of a language for academics and research projects, while Python’s ubiquity and scalability makes it the language of choice for commercial endeavors). Knowledge of SQL and database technologies is also key.
According to Burning Glass, many data analyst job postings also ask for some combination of “soft skills” (i.e., communication, empathy). Here are some of the skills that pop up most often in postings:
Are data analysts in demand?
According to Burning Glass, data analyst jobs are projected to grow 14.3 percent over the next 10 years, suggesting a pretty high level of continuing demand. Moreover, the current time-to-fill open data analyst positions is 34 days, which suggests the current demand for this role is also high.
However, keep in mind that a generalized level of demand doesn’t mean it’s easy to land a job. As the market has seen with data scientists, a high level of demand can translate into more students deciding to enter a particular field.
The more entrants to the field, the more competition for entry- and mid-level positions. As that competition intensifies, the true differentiator is your skills; employers will pay top compensation for those data analysts with the right combination of knowledge and experience to actually get things done.
Are data analysts paid well?
Data analyst salary, as we mentioned above, is heavily dependent on factors such as experience and years of education. Let’s take the latter first; here’s how Burning Glass breaks down data analyst salary by educational attainment:
In a surprising twist, many data analysts with a bachelor’s degree are earning roughly the same as their colleagues with a master’s degree, at least until you get into the upper quartiles.
Now let’s look at experience:
As with so many positions in tech (and beyond), experience inevitably yields a bigger salary. However, it’s incumbent upon experienced data analysts to keep their skills up-to-date, especially as analytics tools can evolve rapidly.
Do I need a degree to become a data analyst?
According to Burning Glass, some 90.2 percent of data analyst positions ask for a bachelor’s degree, suggesting that the vast majority of data analysts don’t need an advanced degree to craft a viable career.
But a degree is just part of the education equation. Do data analysts need certifications? While some employers definitely ask for them, they’re not required for every position.
Here are some popular data-analyst degrees that can help you stand out when you’re applying for a new position (or allow you to negotiate a significant salary bump for your current job):
- CCA Data Analyst
- SAS Certified Data Scientist
- Data Science Council of America Certification
- Microsoft MCSE: Data Management and Analytics
As with many tech positions, employers are placing a premium on experience and skills. Whatever your degrees, your interview process will likely involve assessments to determine whether you can execute the analysis required.
In addition, an interviewer will almost certainly probe your “soft skills,” as a big part of the data analyst job involves communicating effectively with other stakeholders and securing buy-in. Some example questions include:
- How well they communicate with stakeholders.
- Their skill with various types of data analytics software.
- Their approach to data-analytics projects.
- How they handle pressure (complete with examples).
- What they like about data analytics.
Being able to provide answers that draw heavily upon your experience is crucial here. Even if you’re brand new to the data analytics scene, you can still highlight what you’ve learned and independent projects you’ve pursued as evidence that you have what it takes to crunch data for insights.