Data is transforming businesses and accelerating company growth in a way that has never existed before. Jobs within the data science world — especially in the field of data analytics — are on the rise, and there is a steady growth in job demand and compensation year-over-year.

Maybe you’re an aspiring data analytics professional, looking to establish your first real data career. Perhaps you’re looking for opportunities to deepen a current data-related role, or take the next step toward a promotion in a field like data analytics, data science or data engineering.

Consider this article your guide to the top-paying data careers.

Why choose a data analysis job?

The majority of data analysis jobs will command high-median salaries, even in entry-level positions for recent graduates, or people with only a year or two of qualified experience.

Here are a few of the other reasons you might want to consider establishing yourself in a data-related field:

  • A wide variety of job opportunities
  • Ample room for career advancement
  • Daily brainstorming and problem-solving work
  • A balance of technical work and interpersonal communication
  • Few mandatory qualifications

Ready to figure out which data analysis job is best for you?

Let’s dive in.

Best data analyst jobs

The data analysis positions we’ll discuss below are not the only jobs available in the field; they’re also the highest-paying data professions available.

These jobs are ranked from lowest-to-highest salary, but keep in mind these estimated salaries have been derived from a selection of statistics, and may vary based on your individual experience as well as per company compensation packages.

6. Data Engineer ($70,000–$130,000)

A data engineer’s role is to make data more accessible for data scientists and business analysts alike.

Duties within this job include:

  • Building systems to collect, store and analyze data
  • Implementing algorithms to manage and organize data
  • Interpret trends and identify ways to improve data quality and efficiency
  • Optimizing existing systems for more efficient data collection

To become a data engineer you’ll need strong skills in coding, data analysis, database systems and critical thinking.

5. Data Warehouse Engineer ($85,000–$150,000)

A data warehouse engineer is a mega-data engineer; they are responsible for building massive databases that collect and store information from multiple sources.

Duties within this role are similar to those of a data engineer, but on a larger scale. Duties also include additional managerial-like responsibilities, such as monitoring performance, establishing new procedures and problem-solving.

In addition to a bachelor’s degree in computer science, engineering or a related degree, you’ll need communication skills, computer program fluency and at least two years of relevant experience.

4. Data Scientist ($90,000–$175,000)

Data scientists are on the more-informed end of data analysis, with responsibilities to assess data on a very technical level.

Some of the responsibilities associated with the data scientist role include:

  • Identify valuable data sources
  • Process structured and unstructured data
  • Analyze trends and data patterns;
  • Conduct data studies and experiments

In addition to needing a relevant degree as well as experience, data scientists require skills in statistics, advanced mathematics, data mining techniques and computer science.

3. Business Intelligence (BI) Architect ($100,000–$190,000)

A business intelligence (BI) architect is a top-level BI analyst who deals with a wide variety of data to help companies make strategic business decisions.

Responsibilities within this role typically include:

  • Analyze and optimize data structures
  • Diagnose and resolve data issues
  • Provide business intelligence support
  • Provide expert data-driven guidance to a company’s executives

To become a BI architect, you typically need a master’s degree in computer science or engineering, though sometimes a bachelor’s degree will suffice. You’ll also need at least a few years of experience in the role.

2. Big Data Engineer ($110,000–$200,000)

A big data engineer’s primary role is to oversee and manage the large data infrastructures they are responsible for building.

Their duties are nearly identical to a data engineer’s, but on a much larger scale.

Big data engineers must have a degree in computer science or engineering, be skilled in areas such as data architecture, database optimization, high-level programming, and have significant experience in their field.

1. Data Architect ($125,000–$225,000)

A data architect is the visionary behind the data infrastructures that data engineers bring to life.

Some of their responsibilities include:

  • Conceptualizing and designing the blueprint for data framework
  • Collaborating with data scientists to ensure their design will properly organize the data
  • Providing technical guidance and insights to the data engineers
  • Identify ways to optimize a company’s database system performance

You’ll need a relevant degree to become a data architect, and fluency in database structure principles. You’ll also need a knowledge of data mining, and proficiency in operating a variety of technical software.

Accelerate your data analysis career today

At Pace, our mission is to provide every skill and every bit of knowledge a data candidate needs to begin a data analysis career.

As an online education platform that offers highly curated, accelerated success-driven bootcamps that teach today’s most in-demand skills and tactics.

Data literacy training offers a variety of benefits, such as:

  • Better communication with coworkers and clients
  • Smoother, more efficient inner-company operations
  • Strengthened ability to make data-driven decisions
  • Increased revenue and overall company success

Our Data Analytics Program is ideal for aspiring data professionals looking to fine-tune their data analytics skills, and for current data professionals looking to deepen their knowledge of analytics best practices.

Call our Solutions team today to set yourself up for success in the data analysis field.