Data Engineer Jobs: What You Do and Which AI Degree Gets You Hired

Data engineers build the pipelines and databases that deliver data to analysts and AI models. It is a good job to aim for with an AI degree, because models are only as useful as the data feeding them. BLS counts data engineers with database architects, whose May 2025 median pay is $139,500 a year. Most entry-level jobs ask for a bachelor’s degree.

What Does a Data Engineer Do All Day?

Picture a company with sales records, website clicks, sensor readings and customer emails, all stored in different places and formatted differently. A data engineer makes that mess usable. You build the systems that pull the data in, clean it, store it and hand it to the people who need it.

BLS does not publish a data engineer occupation. It counts the work with database architects, so these figures cover that wider group. O*NET, the federal job database, lists data engineer as an alternate title for the same occupation.

BLS lists these duties for database architects:

• Identify user needs to create and administer databases.
• Design and build new databases.
• Ensure that organizational data are secure.
• Back up and restore data to prevent data loss.
• Ensure that databases operate efficiently and without error.
• Make and test modifications to database structure when needed.
• Research technical requirements, create models, code new data architecture, integrate existing databases, and check for errors.

In practice, a normal week mixes building and fixing. You might write a pipeline that loads a new data source, then spend a morning finding out why last night’s job failed. You talk to data scientists about what they need and to security staff about who can see what.

It is quieter work than building models. People notice you when something breaks, and that is the honest downside. The upside is that nearly every AI project depends on you.

Why Does an AI Degree Lead to Data Engineering?

An AI degree teaches you how models learn from data. A data engineer makes sure that data arrives on time, in the right shape, and without errors. Those two jobs sit next to each other on most AI teams.

Many people who study AI discover they like the plumbing more than the modeling. Others pick data engineering first because the hiring bar for a bachelor’s is clearer. Both are fine.

Be realistic about one thing. Most AI degrees spend more time on machine learning, deep learning and language models than on databases and pipelines. In our program data, a few programs name data engineering, big data or MLOps in their coursework. You will likely need to fill gaps with SQL and cloud practice on your own.

If you are still deciding between AI work and other technical paths, our guide to AI careers compares the main roles, and our page on becoming an AI engineer covers the neighboring job.

Which Degree Level Do Employers Expect?

BLS lists a bachelor’s degree as the typical entry education for this group, and it says graduate school is not required. Typical is not the same as required. Employers set their own rules, and many accept experience in place of a degree.

That points to a simple map of which AI degree fits which starting point.

You have no degree yet. An online bachelor’s in AI is the usual match. Our online AI bachelor’s ranking shows programs by cost and format. Western Governors University’s online BS in AI Engineering charges $4,200 per six-month term, so finishing faster costs less. Dakota State’s online AI bachelor’s totals $44,856 before fees.

You have a bachelor’s in another field. A master’s or a graduate certificate fills the gap. Browse the online AI engineering degrees for programs that stress building systems, or the online applied AI degrees for practical programs that fit working adults.

You are already a developer or analyst. A short certificate may be enough. The Brandeis applied machine learning and engineering certificate lists a course called Data Engineering and Cloud Pipelines. It is fully online, totals $14,640 for 12 credits and does not require the GRE.

You want to work on ML infrastructure. Look at the online machine learning degrees. Check the course lists there for big data and pipeline coursework.

What Does a Master’s Add?

The master’s costs more and takes longer, and BLS does not say it raises pay for this group. What it can do is open doors if you are switching fields or want to work on AI platforms. Our online AI master’s ranking compares programs on price and format.

Prices vary widely. The University of Texas at Austin’s online MS in Artificial Intelligence totals $9,990 for 30 credits. The University of Illinois Chicago’s online MEng with an AI and machine learning concentration totals $32,256 before fees. Duke’s online AI for Product Innovation master’s totals $76,650 and has two required campus residencies.

Course lists are the best clue to fit. Duke lists Sourcing Data for Analytics and Operationalizing AI (MLOps). The University of Arizona’s AI for Business master’s lists Big Data Technologies. The University of North Texas lists Introduction to Big Data and Data Science. Capitol Technology University lists a Big Data course. Check the current catalog before you apply, because schools change courses.

What Skills and Tools Do Data Engineers Use?

Postings differ by employer, so treat this list as a starting point and read a few real job ads in your city. The skills below come up most often in this kind of work.

• SQL. You will write it constantly. Learn joins, window functions and how to read a query plan.
• Python. It is the usual language for building pipelines and checking data.
• Database design. Know how to model data for fast reads and for reliable writes.
• Cloud platforms. Most companies store data with a major cloud provider, so pick one and get comfortable with it.
• Pipeline tools. You will see workflow schedulers, streaming systems and transformation tools named in postings.
• Security and backups. BLS lists both as core duties, so understand access controls and recovery.
• Communication. You will translate between analysts, scientists and managers all the time.

An AI degree adds one more useful skill. You understand what a model needs from its training data, so you can build pipelines that serve it instead of guessing.

How Do You Get Hired as a Data Engineer?

There is no single path, but this order works for most people.

1. Pick your degree level. Use the section above. If you already have a bachelor’s in a technical field, you may only need a certificate.
2. Learn SQL and Python well. Do this before anything else. Everything else builds on them.
3. Take the data courses your program does not cover. If your AI program skips databases and pipelines, add them with a short course or self-study.
4. Build two or three real projects. Pull data from a public source, clean it, store it in a database and schedule it to refresh. Put the code and a short write-up online.
5. Get close to the work. Apply for analyst, junior developer or database roles if a data engineer title is hard to land first. Many people move over after a year or two.
6. Apply with a specific story. Say which pipeline you built, what broke and how you fixed it. Hiring managers remember that.

An internship helps. Some programs on our list include internships or industry projects, so check each program page for details.

How Much Do Data Engineers Earn?

BLS counts data engineers with database architects, so these figures cover that wider group. Do not read them as AI-specific pay. The May 2025 survey counted 67,140 workers in this occupation.

• Median annual wage: $139,500, or $67.07 an hour.
• Mean annual wage: $144,440.
• 10th percentile: $86,240.
• 25th percentile: $109,370.
• 75th percentile: $169,290.
• 90th percentile: $204,000.

The middle half of workers earns between $109,370 and $169,290. The 10th percentile mixes new and experienced workers, so it is not a starting salary.

Location matters. By annual mean wage, the top-paying states are California at $175,330, Massachusetts at $163,290, Virginia at $154,550, Connecticut at $154,520 and the District of Columbia at $149,300. The biggest job markets are Texas with 8,270 workers, California with 6,210, Virginia with 5,260, North Carolina with 4,070 and New York with 3,850.

Our data engineer salary page has the full state table, the cost of an online AI degree next to these wages, and what moves pay up or down.

What Is the Job Outlook?

BLS projects employment of database architects to grow 9 percent from 2025 to 2035 and describes that as much faster than average. It counted 69,500 of those jobs in 2025.

BLS also publishes openings for database administrators and architects together: about 7,300 a year, with 6,500 jobs added across the decade. The combined group is projected to grow 4 percent from a base of 144,500 jobs. Those openings include people who leave the field, not only new roles.

Projections are estimates, and BLS revises them each cycle. They describe a federal occupation, so they will not match every employer’s data engineer openings.

What Does the Work Feel Like Day to Day?

Expect a lot of reading and debugging. Much of the job is tracing where a number came from and why it changed. You will sit in meetings where someone says the dashboard looks wrong, and you will be the person who finds out whether the data or the dashboard is at fault.

It suits people who like order. If you enjoy making a messy system tidy and reliable, you will probably like it. If you want to be the one who trains the model and presents the results, a machine learning role may fit better.

Can You Do This Job Remotely or With an Online Degree?

Both are possible, with limits. Most online AI degrees on our list are fully online, and a few require campus visits. Duke’s program, for example, has two residencies, so read each program’s page.

For remote work, the answer depends on the employer. Our data tracks degrees, not job postings, so we cannot tell you what share of data engineer roles are remote. Check every posting for its policy, because some employers cut pay for workers outside a high-cost city.

Employers care most about whether you can show working pipelines. An online degree from an accredited school plus a few real projects is a normal route in.

What Should You Do Next?

Decide where you are starting from, then match it to a degree level above. Open the AI engineering rankings if you want to build systems, or the machine learning rankings if you lean toward modeling.

Before you commit, read the course list for anything about databases, cloud, big data or MLOps. Then look at five job ads for data engineers in your area and compare the skills they list. That tells you more about what to study than any degree title does.