Data Engineer Job Outlook 2025 [Research on 1,000 Job Postings]

In 2023, we churned out 132 zettabytes of data worldwide. To put that in perspective, that's a whopping 132,000,000,000 terabytes. We're living through what you might call a data gold rush, and smart businesses aren't missing out. 

To manage this massive amount of data and ensure it reaches the right teams for analysis, companies rely on data engineers who build essential data pipelines that transform raw information into useful assets.  

But how’s the data engineer job market in 2025?  

According to StartUs's 2025 report, the data engineering sector now employs over 150,000 professionals, with more than 20,000 new jobs created in the past year. 

Data isn't going anywhere—in fact, it's only growing. If you're looking for an in-demand career with room for progress, data engineering might be for you. 

This article is here to bring you insights into the 2025 data engineer job outlook. 

As part of our annual research series on data and AI job markets, we've analyzed 1,000 job postings to reveal what employers seek in data engineers for 2025—helping you stay ahead of the curve. 

Key Insights 

• Python (70%) and SQL (69%) are core pillars, but having an additional language like Java (32%), Scala (25%), or Kafka (24%) on your CV signals strong versatility. 

• Apache Spark remains the dominant framework (38.7%), but platforms like Snowflake (29.2%) and Databricks (16.8%) are quickly carving out their own territory. 

• Data engineers are expected to work across both relational and NoSQL databases. While Amazon Redshift (21.8%) leads, the demand for skills in Cassandra, MongoDB, and DynamoDB highlights the need for flexibility. 

• Data visualization is creeping into the data engineer's scope — about 1 in 10 job postings now require Tableau, Power BI, or a similar tool. 

• Most jobs require 2–6 years of experience. Senior roles (6+ years) are a minority, suggesting that teams are either scaling fast or investing in mid-range hires. 

• A bachelor's degree is still the baseline, appearing in 74% of postings—though 42% specifically require only a bachelor's. But 26% of job ads don't even mention education, showing a shift toward skills-first hiring. 

• DevOps is clearly becoming part of the data engineer's daily life. CI/CD is mentioned in nearly 1 out of 6 postings. 

Table of Contents 

• ​Methodology 
• ​What Does a Data Engineer Do? 
• ​How Can You Become a Data Engineer? (Education)
• ​What Technical Skills Do You Need as a Data Engineer? (Skills & Tools)
• ​How Can You Land a Data Engineer Job? (Locations, Salaries & Experience)
• ​What is the Data Engineer Job Outlook in 2025? 
• ​Become a Data Engineer with 365 Data Science 
• ​FAQs​ 

Methodology 

Our analysis covered 943 data engineer job postings from Glassdoor US to provide a comprehensive view of the data engineering job market in 2025. 

We carefully cleaned our data and analyzed key data engineer requirements, skills, and technologies from each posting. This thorough examination gives us insights into current job responsibilities and industry demands. 

To present our findings effectively, we've converted raw numbers into percentages and created data visualizations that showcase the most significant patterns and trends in the field. 

Wondering how to become a data engineer in 2025? Let’s start examining the results. 

What Does a Data Engineer Do? 

Based on our extensive job market analysis over the years, we've noticed an interesting trend in how companies hire for data-related positions. 

Rather than seeking specialists who focus on narrow aspects of data handling, many companies prefer versatile professionals capable of managing the entire lifecycle of data operations with expertise across multiple domains. 

To better understand this evolution in hiring preferences, we've created our Job Posting Specialization Score (JPSS). But first, to help us compare, let's look at the standard data engineer job description. 

Data Engineer Job Description 

Data engineers design, develop, and maintain the systems and infrastructure that collect, store, and process large volumes of data. They are the architects behind an organization's data pipelines, making sure data flows smoothly from various sources to where it needs to go. 

In 2025, the data engineer career is essential in data-driven organizations. They collaborate with data scientists, analysts, and business stakeholders to keep data accessible, reliable, and ready for analysis. 

The role typically requires: 

• Strong programming skills in SQL and Python 

• Expertise in data warehouse solutions and ETL processes 

• Experience with big data technologies (Hadoop, Spark) 

• Knowledge of database design and architecture 

• Proficiency in cloud platforms (AWS, Azure, GCP) 

While data analysts focus on interpreting data and data scientists create predictive models, data engineers build and maintain the foundation that makes their work possible. 

Job Posting Specialization Score (JPSS) 

But how does this standard description match up with what employers actually want in 2025? To find out, we created the Job Posting Specialization Score (JPSS). 

The JPSS measures whether companies are looking for specialists or generalists by analyzing how many different skill areas each job posting requires. This helps us understand there is demand for data engineers with deep expertise in specific areas or those who can handle a broader range of tasks. 

We analyzed job postings across 11 skill categories and assigned each posting a JPSS based on required skills. Here's how we broke down the categories: 

Here are the results:  

Earlier this year, we released our ML engineer job market research, which showed the closest split between Domain Experts and Versatile Professionals. Data engineers have now claimed this top spot, with an almost perfect 50/50 split. 

This trend indicates that companies are blurring boundaries between data roles. As organizations—particularly smaller businesses—look to streamline their data operations and reduce costs, they increasingly look for data engineers who can wear multiple hats. 

These versatile professionals can not only build robust data pipelines but also perform preliminary data analysis, create basic visualizations, and understand the business implications of their technical decisions—making this an important consideration for the future of data engineering. 

Our 2025 research found that data scientists stand out as the role with the highest proportion of Versatile Professionals. Meanwhile, AI engineers and data analysts tend to be more specialized in their skill sets. 

The reason for this lies in how companies use these job titles. Many employers treat ‘data scientist’ and ‘data engineer’ as umbrella terms that cover multiple responsibilities throughout the data lifecycle. This doesn’t seem to be the case with other data and AI roles we’ve analyzed. 

That being said, with half of all job postings looking for specialist data engineers, there are still plenty of opportunities for those who've developed deep data engineering expertise. 

So, the answer to the question "What is a data engineer?" might not be as straightforward as it seems. 

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How Can You Become a Data Engineer? 

How can you become a data engineer in today’s job market? Let’s look at what education and qualifications employers are really looking for in 2025. 

Data Engineer Education Requirements 

Our analysis of data engineer education requirements in 2025 reveals that employers value both formal credentials and practical experience. 

But it’s important to keep in mind that, in a highly technical field like data and AI, many employers consider a data engineer degree crucial.  

Our 2025 analysis shows engineering degrees appearing in 77% of job postings, followed by computer science and data engineering at 45% each. 

This represents a notable shift from 2024, when data engineering led at 49%, followed by computer science (39%) and engineering (29%)—with none exceeding the 50% mark. 

The trend shows a clear pivot toward broader technical degrees, particularly engineering, which now appears in three-quarters of all postings, while specialized data engineer degrees have become less emphasized. 

Interestingly, this trend contrasts with what we've observed in other roles this year. Most notably, ‘data science’ degrees have surged in importance for data scientist positions, with mentions appearing in 70% of job postings. 

For data engineers, this trend reflects how data infrastructure has become more complex and interconnected. Companies seek data engineers with broad technical foundations to manage components like distributed systems and DevOps practices. While core data engineering skills are essential, specific expertise can be learned through experience. 

Another important factor to consider is degree availability. Data engineering has not yet established itself as an official degree at most universities, and when it does appear, it's typically only as a master's program. 

To sum up, if you're considering what degree to pursue for data engineering, engineering or computer science are your best options. 

Nevertheless, our analysis found many other degrees on the list, including related fields like machine learning, statistics, mathematics, and AI. We also saw less related fields such as architecture, physics, and economics. This shows that many fields provide overlapping skill sets, and specialized skills can always be learned later through online certification programs.  

In other words, based on our data engineer job market research, transitioning into this career is highly achievable for professionals from various backgrounds. 

You can enhance your bachelor's degree with targeted certifications from our learning platform 365 Data Science—we offer all the topics you need to secure a job this year! 

Now that we’ve covered the most relevant fields of study, let's examine what level of education companies require when hiring data engineers in 2025. 

As we saw last year, bachelor's degrees remain the most sought-after level of education for data engineers in 2025, required in 42% of job postings. Master's degrees are also popular, appearing in 28% of postings. PhDs, however, remain a non-requirement for data engineering, showing up in less than 5% of postings. 

Also like last year, roughly a quarter of job postings don't specify any degree level requirement—this percentage has actually risen from 23% to 26%. 

Although this trend doesn't guarantee that employers will overlook formal education entirely, it indicates that self-taught professionals could have a chance at landing these roles. 

What matters most in the tech sector is demonstrable expertise. With dedication to learning, consistent practice, and a strong portfolio showcasing your abilities, you can thrive in a data engineering career, regardless of your educational background. 

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What Technical Skills Do You Need as a Data Engineer? 

While academic qualifications are important, employers value practical skills and hands-on experience above all—particularly when candidates can showcase their abilities. Let's explore the key skills that hiring managers look for in data engineers in 2025. 

Programming Skills for Data Engineering 

Programming forms the foundation of data engineer skills, as it allows professionals to build and maintain complex data systems that power data-driven decision-making. 

The top three programming languages remain unchanged since last year. In 2025, Python is mentioned in 70% of data engineer job postings, followed by SQL at 69% and Java at 32%. 

One interesting change since last year is the decrease of SQL mentions. In 2024, SQL appeared in 79% of postings—6% ahead of Python. Now, the two programming languages hold similar levels of importance among employers. 

While not a huge change, this shift may reflect the growing popularity of tools like SQLAlchemy and pandas, which allow data engineers to work with databases using Python code instead of writing raw SQL queries. 

Regardless, these three languages are important data engineering skills employers look for. Why? 

• Python's user-friendly nature and powerful libraries let engineers quickly build data pipelines and automate tasks. 

• SQL is the bread and butter of database work—you simply can't avoid it when you're managing and pulling data from databases. 

• Java might seem like the odd one out, but it's the go-to choice when you need to build solid, high-performance systems that can handle massive amounts of data. 

Most data engineers end up using all three languages regularly, each one being the right tool for specific jobs. 

Kafka and Scala also appeared in roughly a quarter of data engineer job postings each, making them valuable skills to learn if you already have the core three languages in your toolkit. 

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Data Engineering Skills 

Beyond programming languages, data engineers need proficiency with specific tools and technologies that help them build and maintain data infrastructure. Here's what our analysis of the job market in 2025 reveals about the most in-demand data engineering technologies. 

Data Engineering Tools & Frameworks 

In data engineering, tools and frameworks are the technologies that allow professionals to design, build, manage, and optimize systems that handle huge volumes of data. 

Tools often refer to software or platforms used for specific tasks like data ingestion (e.g., Apache NiFi), orchestration (e.g., Airflow), or ETL (e.g., Informatica). 

Frameworks typically provide a more structured environment or API for processing data, such as Apache Spark or Hadoop. 

Here are some of the top tools and frameworks you need to know to become a data engineer in 2025. 

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Databases 

Databases are the foundation of data infrastructure, storing and managing all types of data. Here's a quick look at the main types: 

• Relational databases (PostgreSQL, MySQL, SQL Server) use structured tables with set schemas for reliable, complex queries. 

• NoSQL databases (MongoDB, Cassandra) provide flexible, scalable solutions for large-scale and real-time data needs. 

• Cloud-native databases (BigQuery, Redshift) are great at processing massive datasets with minimal maintenance. 

Data engineers pick the right database based on their specific needs for performance, scalability, and how it fits into their existing systems. 

Here are the top database technologies required for data engineer skills in 2025:  

Data Modeling and Architecture 

Data modeling and architecture refer to the planning and structuring of how data is collected, stored, accessed, and managed. 

Data modeling defines how data is organized through models, making sure it’s consistent and query-ready. 

Data architecture focuses on the systems and infrastructure—like data lakes and warehouses—that support data flow, storage, and analytics. 

Together, they keep data accurate and accessible to the right stakeholders at the right time—making them crucial functions of a data engineer career. 

Let’s look at some of the relevant skills for data engineer careers this year: 

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Data Orchestration & Automation 

Data orchestration and automation help manage and schedule how data moves between systems. 

Orchestration helps manage complex data pipelines by making sure all tasks run in the right order and work together properly. 

Automation takes care of regular tasks (like daily data updates) without needing someone to run them manually. 

These tools help create reliable and efficient data systems that can handle large workloads with fewer errors. 

Let’s look at what kinds of skills employers look for in the 2025 data engineer job market:  

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Cloud Skills for Data Engineers 

Now that we’ve look at the key data engineering skills in demand for 2025, let's explore one of the industry's most significant developments in recent years: cloud computing. 

Instead of managing servers themselves, data engineers use cloud services that provide everything they need—from computing power to databases. 

These platforms make building and running data systems much easier and more cost-effective. They come with built-in tools for common tasks like data processing, automation, and analysis, which saves time and reduces complexity. 

Here are the top cloud platforms on the data engineer job market in 2025. 

Our 2025 data reveals an interesting data engineering job trend: AWS has maintained its strong position in the data engineer job market, while Microsoft Azure's presence has declined. Last year, Azure appeared in 75% of job postings, but this has dropped to just 34% in 2025. 

We saw this pattern consistently across our job market research for 2025, including data scientists and ML engineers. Based on these trends, AWS seems to be the most practical platform to begin your cloud journey. 

In fact, AWS certification was also the most frequently mentioned cloud credential, appearing in 4.2% of listings, while Azure certifications appeared in 3.6% and Google Cloud certifications in 1.2%. 

Want to learn cloud computing—a must-have skill for your data engineer career? Our Understanding Cloud Computing course covers core concepts, industry trends, and career paths in cloud technology. Start your cloud journey today! 

DevOps for Data Engineering 

DevOps brings together developers and operations teams to ship better software faster. It streamlines work through automation, cloud setups, and smart monitoring systems. 

Data engineers rely heavily on DevOps practices to build and maintain data processing systems. Their projects need strong cloud infrastructure and automated pipelines to keep data flowing smoothly and catch any issues before they become problems. 

Here are the key DevOps skills employers are seeking according to our 2025 data engineer job outlook research. 

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Interdisciplinary Technical Skills 

As our research over the past few years shows, employers are increasingly looking for versatile data professionals with broad skill sets. 

According to the JPSS, about half of the data engineer job postings in 2025 sought candidates with wider technical capabilities. 

One of the most notable interdisciplinary skills that appeared frequently in these postings was data visualization. 

Data Visualization for Data Engineers 

Though not traditionally part of the data engineer career, companies value data visualization skills. They expect data engineers to not only process data but also help present it effectively to stakeholders and visually inspect data pipeline outputs. 

Here are the top data visualization tools in the data engineer job outlook 2025. 

For both aspiring and experienced data engineers, learning data visualization could be a valuable addition to your skillset in the 2025 data engineer job market. 

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How Can You Land a Data Engineer Job? 

Now, let’s examine two crucial factors from our data engineer job market analysis: where these jobs are located and their salaries. 

Where Do Data Engineers Work? 

When you think about tech jobs, Silicon Valley is probably the first place that comes to mind. But our data suggests that California might no longer be the primary hub for data professionals in the job market right now. 

As of 2025, Texas has surpassed California in available data engineering jobs, with Texas holding 26% of postings compared to California's 24%. 

This shift is driven by several factors: 

• Business-friendly policies, including no state income tax and lower corporate taxes, make it attractive for companies. 

• Booming tech hubs like Austin, Dallas, and Houston are home to major employers such as Apple, Oracle, and Tesla. 

• A strong local talent pool from top universities and a lower cost of living help companies recruit and retain engineers more easily. 

• Remote and hybrid job growth also favors Texas for its central time zone and tax advantages. 

Altogether, Texas offers the ideal mix of affordability, skilled talent, and good business conditions—making it one of the fastest-growing states for data engineering careers. 

Having said that, California still maintains nearly a quarter of job postings. Other states in the top 10 include Virginia, New York, Washington, Illinois, Massachusetts, Florida, New Jersey, and Arizona—though none account for more than 10% of postings. 

Now, let's get into what you've all been waiting to hear. 

Remote Work for Data Engineers 

One of the most dramatic shifts in 2025 has been the decline in the number of employers offering fully remote positions. Last year, 10% of job postings were remote—that number has plummeted to less than 2% in 2025. 

We saw similar shifts away from remote work across all our other job market research this year—including a comparable 10% decline for ML engineers. 

The workplace landscape has evolved significantly in 2025. According to recent data from Statista, hybrid work arrangements have become the standard, with half of US professionals dividing their time between remote and office work. 

While fully remote positions for data engineers have decreased dramatically, most companies now embrace a balanced approach. 

So, for those pursuing a career in data engineering, expect to be within commuting distance of your workplace. 

How Much Do Data Engineers Make in 2025? 

According to Glassdoor data from early 2025, the average data engineer salary is \$130,000 annually in the US. 

This, however, is the average—your salary depends on your location, company, and years of experience. Here’s a more detailed breakdown, from entry-level data engineer salaries to upper-management roles. 

0-1 Year: \$106,000 

2-3 Years: \$116,000 

4-6 Years: \$133,000 

7-9 Years: \$143,000 

10+ Years: \$153,000+ 

In 2025, Glassdoor reveals an unexpected trend: both data engineers and machine learning engineers have experienced salary decreases. The average data engineer salary has dropped significantly from \$153,000 in early 2024 to approximately \$133,000 in 2025. 

Our 2025 data engineer job market research agrees in the average range, but it doesn’t necessarily indicate a salary drop. We found that most positions (30%) offer salaries between \$120,000 and \$160,000. The second most common range is \$100,000 to \$120,000 at 17% of postings, while positions paying between \$160,000 and \$200,000 make up about 15% of listings. 

Comparing this with our 2024 data shows an upward trend in salaries. Last year, the third most common salary range was \$80,000 to \$100,000—this spot has now been taken by \$160,000 to \$200,000. This shift indicates that more jobs are offering higher salaries than last year. 

While Glassdoor's data shows a salary decrease, this may not accurately represent current market conditions. Since Glassdoor's data comes from voluntary user submissions, it can lag behind real-time data engineer job trends and may not capture the full picture. 

Our analysis of active job listings indicates that data engineering compensation continues to be competitive, with many positions offering higher salaries than Glassdoor's early 2025 data suggests. 

How Much Experience Do Data Engineers Need? 

In 2025, the most commonly required experience level is 2-4 years, appearing in 17% of job postings. This is followed by: 

• 4-6 years - 15% 

• 6-8 years - 5% 

• 8+ years - 4% 

• 0-2 years - 2% 

The data shows that companies predominantly look for mid-level professionals with 2-6 years of experience. Entry-level candidates may need to consider alternative roles—like internships or junior analyst positions—to gain initial experience. 

What's interesting is that around half of the data engineer job listings we looked at don't mention a specific experience requirement. This suggests companies care more about what you can actually do—your skills and portfolio—rather than how many years you've been in the field. 

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What is the Data Engineer Job Outlook in 2025? 

So what's the data engineering career outlook in 2025? Our research shows it remains a stable and rewarding career path. Here are the key trends we've identified: 

• Average salaries are competitive at \$130,000, with most positions offering between \$120,000-\$160,000 

• Texas leads with 26% of data engineering jobs, followed closely by California at 24% 

• Cloud platforms like AWS and Azure are becoming a must—with AWS emerging as the most popular platform this year 

• Programming skills remain vital, with Python, SQL, and Java being the most sought-after languages 

Another notable trend is that employers now seek well-rounded data engineers. Rather than hiring specialists, half of the companies we analyzed seek professionals who can seamlessly switch between building data pipelines, creating visualizations, and managing cloud infrastructure. 

Is data engineering becoming oversaturated? Our findings suggest not. 

According to a StartUs report, the data engineering sector currently employs more than 150,000 professionals, and it added over 20,000 new jobs in the past year. So don’t be afraid to launch your data engineering career this year! 

Become a Data Engineer with 365 Data Science 

At 365 Data Science, we offer a comprehensive Data Engineer Career Track designed to transform beginners into job-ready professionals. Our carefully structured 10-course curriculum covers all the skills highlighted in this data engineer job outlook report—from SQL and Python programming to advanced data pipeline development with Apache Airflow. 

Our curriculum is specifically designed to meet current data engineer job requirements, ensuring our courses prepare you for the technical demands of the role. 

The Career Track includes essential courses like Data Ingestion with pandas, Understanding Cloud Computing, and Data Architecture, plus you can complete hands-on projects that simulate real-world data engineering challenges. You'll learn to build and maintain data pipelines while creating a portfolio that showcases your practical skills to potential employers. 

Ready to start your data engineering career? Join our Data Engineer Career Track and learn alongside thousands of aspiring professionals. With expert-led courses, hands-on projects, and industry-recognized certification, you'll be ready to tackle real-world data engineering challenges in no time. 

We hope this data engineer job outlook has helped you understand the opportunities and requirements for landing your dream role in 2025! 

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