Top Companies for Data Engineer Jobs 2025

The demand for everything data has skyrocketed in the past couple of years and gained even more speed in 2024. While data-driven strategies were becoming popular within large organizations either way, the surge in popularity of generative AI, ChatGPT, and other more advanced LLMs made data-based company decisions a must-have in 2024.

Because of this, we see a huge increase in data engineer jobs, and while the supply still can’t meet the demand, you, as a data engineer, might have the freedom to choose your company.

But which company is actually the best option for a data engineer right now? In this article, we will recommend a list of companies based on benefits, salary, work-life balance, and other amenities.

Let’s get into it!

Data engineers are the backbone of everything related to data. They transform raw data into a much cleaner and usable form that data analysts or data scientists can then analyze.

This system leads businesses to make the right data-driven decisions. So, data engineers have a big responsibility—which is why only the best get to land this role.

With that in mind, let’s look at what companies have to offer these incredibly skillful data brainiacs.

Working at Google has to be a data engineer’s dream job—and for a good reason. It’s no secret that Google (or Alphabet) is one of the world’s largest companies working with unruly amounts of data. It’s also one of the biggest tech leaders in the world.

In fact, a huge percentage (77%) of their profits are from ads, and many of them are targeted ads based on user data.

This positions Google at the forefront of managing some of the world’s datasets, allowing you, as a data engineer, to also work at the forefront. Data engineers will be privileged to access some of the most advanced methods for statistical analysis, bleeding-edge tools, and more.

In other words, data engineers at Google have a tough job and a lot of responsibilities, but they also have a lot of fun and opportunities to learn and further improve their skill sets.

The Positives for Data Engineers at Google

Here are some benefits and amenities you can experience at Google and the reasons why so many people dream of working for this company:

• Access to World-Class Tools: Google develops tools like BigQuery and TensorFlow, allowing engineers to work directly with some of the best technologies in the industry.
• Career Growth Opportunities: With Google’s global reach, data engineers can explore diverse roles and career paths, including transitioning to data science, machine learning engineering, or leadership positions.
• Opportunities for Engineers: Google encourages continuous learning, offering internal courses on cutting-edge technologies and collaboration with teams working on AI and ML integrations.
• Industry Recognition: Having Google on your resume enhances your credibility and can open doors to future opportunities in tech.
• Comprehensive Compensation and Perks: Google offers competitive salaries, stock options, generous bonuses, and perks like healthcare, 401(k) matching, and wellness programs.
• Flexibility and Work Culture: Google emphasizes flexibility, including hybrid work options, and fosters an inclusive, innovative culture where employees are encouraged to share ideas and collaborate.

The Negatives for Data Engineers at Google

Even though Google is a tech leader and provides ample opportunities for data engineers, there are still some downsides to landing a job there. Here are a couple of them:

• High-pressure Environment - working for a tech giant like Google means you always have to give 100%. The expectations are very high, especially for data engineers, since they have critical obligations, so even small mistakes can have high stakes.
• Difficult to See the Bigger Picture - In an organization as large as Google, you might find yourself working on very specific tasks, which limits your view of the project, i.e., the bigger picture. This can be a bit disheartening because you might not feel the impact of your work on the end product.
• Competitive Environment - at Google, everyone tries to stand out, so advancing your career within the company can feel like a never-ending battle. Despite their contributions, some employees feel overshadowed or stuck in a slow promotion cycle.

Spotify is the biggest music platform in the world, and it’s known to provide one of the most curated playlists based on users’ preferences. You listen to just one song, and then you get suggested dozens of artists that fit the style of that one song.

This process of personalizing every unique account requires going through a lot of data. Now, scale that data for 640 million active users; you can imagine how large the datasets can get. This is why Spotify is a good place to land a data engineering job.

The Positives for Data Engineers at Spotify

An organization working with a lot of data does not automatically mean it is a good place for data engineers. So, let’s have a look at the opportunities and benefits of working at Spotify as a data engineer:

• Cutting-edge Technologies - Spotify must use the most advanced technologies to process large amounts of data. As a data engineer, you can get much hands-on experience with machine learning, big data analytics, and more.
• Learning and Development Approach - Spotify has a team called GreenHouse that focuses on ensuring workers within the organization are constantly evolving, learning, and developing their skills to advance their careers further.
• Other Benefits - One thing you can expect from these giant companies is benefits for retirement, parenting, vacation, insurance, etc. At Spotify, you can expect good health insurance and mental health care, a solid 401K plan, and one of the better maternity and paternity leave options out there.

The Negatives of Data Engineers Spotify

Like any other company, Spotify has its downsides as well. Here are some of them:

• Potentially Working with Non-data Teams - There have been a couple of reports of data-related workers ending up in non-data teams, which means management may have unrealistic expectations for the assigned work tasks. This can affect a data engineer’s performance, work/life balance, and general mental health.
• Deadlines and Expectations - Even if you land a job within a data team, the expectations here are enough to exhaust any expert in data. If you don’t think you can handle the pressure of high expectations and deadlines, working at Spotify might not be your best option.

Amazon, one of the largest e-commerce platforms in the world, operates with a customer-first mindset. With its vast operations ranging from retail and AWS (Amazon Web Services) to Alexa and Prime Video, Amazon generates and processes data at an unprecedented scale.

Every click, purchase, or command given to Alexa contributes to a massive dataset. As of 2024, AWS remains the leader in cloud computing and is a primary driver of its profitability. For a data engineer, this allows one to work on large-scale systems that directly impact millions of customers.

Amazon’s focus on data-driven decision-making and its commitment to operational excellence makes it an attractive option for data engineers looking for challenges and growth.

The Positives for Data Engineers at Amazon

Here are some of the reasons why Amazon can be a great choice for data engineers:

• Diverse Data Projects - From optimizing supply chains to building recommendation algorithms, Amazon offers a wide array of projects you can dive into as a data engineer.
• Advanced Tools and Technology - At Amazon, you’ll work with cutting-edge technologies, including AWS tools like Redshift and EMR, a great way to gain expertise in cloud-based data solutions.
• Career Development Programs - Amazon emphasizes upskilling through internal training and certifications, such as the AWS Data Engineering track.
• Ownership and Impact - Data engineers at Amazon are often encouraged to take ownership of projects, providing a sense of accomplishment and influence over large-scale systems.
• Comprehensive Compensation Packages - Amazon offers competitive salaries, stock options, and bonuses. Additionally, benefits like health insurance, parental leave, and discounts on Amazon products add to the appeal.

The Negatives for Data Engineers Amazon

While Amazon offers plenty of opportunities, it does have some drawbacks:

• High Workload and Intensity - Amazon’s fast-paced environment and the “Day 1” culture often result in long working hours and high expectations.
• Customer Obsession Pressure - With Amazon’s commitment to customer satisfaction, data engineers face immense pressure to meet tight deadlines and deliver high-quality results.
• Corporate Size Challenges - Amazon is an overwhelmingly large organization, so it can be difficult to navigate internal hierarchies or see the impact of your work. However, you should expect this from most organizations at this level.

Meta is the parent company of Facebook, Instagram, Threads, and WhatsApp, which means it has to sort through enormous amounts of data. Supposedly, Meta is working with exabytes of data, and a large part of that is for targeting ads since 97% of their revenue is through ads, AI training, AR/VR development, optimizing social platform algorithms, and more.

So, for data engineers, there’s a lot of room for growth here, career paths, and more.

Let’s look at some positives of landing a data engineering job here.

The Positives for Data Engineers at Meta

Based on the experiences of various DEs, here are some positives of working at Meta:

• Work-Life Balance Is Highly Valued - While most tech giants boast about a good work-life balance, their words don’t always hold up. However, for Meta, current or former employees often say positive things about Meta’s approach toward work-life balance. That’s definitely something to keep in mind as a DE.
• Hackathons - Hackathons are taken seriously at Meta, and any potential ideas/winning projects might be shared with the higher-ups and turned into real products. So, if you’re creative, these hackathons are something to consider.
• Open Work Culture - This openness toward work, especially in the data engineering field or data in general, means they expect you to find your own projects to work on. Basically, you can choose your projects and integrate them within any team you want. This means you can start working on older and easier projects, or if you want to show off, you can take on more difficult tasks.

The Negatives for Data Engineers at Meta

DE roles, or work in general in Meta, are often seen as positive experiences, but that’s not to say there aren’t any downsides to Meta. Here are some to keep in mind:

• Excessive Performance Reviews - While performance reviews are necessary for an organization as large as Meta, employees feel they can be too hard at times. If you focus just on your core responsibilities and do a good job, you still might end up with a mediocre performance review because they expect more (social events, team building, contributing to other projects, etc.).
• Expectations Outside of Your Responsibilities - Related to the previous point, the work culture at Meta pushes for socializing. If you’re an introvert and don’t enjoy frequently talking or meeting with new people, this can affect your work-life balance.

Microsoft: Empowering Enterprise Data Solutions

As a leader in enterprise solutions, Microsoft’s Azure platform is central to its data engineering efforts. Engineers work on projects transforming how businesses use data to make strategic decisions.

• Core Innovations - It developed solutions like Azure Synapse Analytics and the integration of AI models into data workflows.
• Learning Opportunities - Microsoft invests heavily in training programs for its engineers, making it an ideal environment for continuous upskilling.
• Tip for Success - Demonstrate experience with enterprise-level data architecture and automation tools.

Netflix: Mastering Data-Driven Creativity

At Netflix, data engineers are instrumental in enhancing the platform’s renowned recommendation engine. Projects often push the boundaries of personalization and content delivery efficiency.

• Unique Challenges - Handling data at a petabyte scale to deliver seamless streaming experiences globally.
• Culture of Innovation - Engineers collaborate with cross-functional teams to iterate rapidly on experimental algorithms.
• Tip for Success - Exhibit strong expertise in real-time data pipelines and tools like Apache Kafka and Spark Streaming.

Landing a job at a tech giant organization requires a lot more than just a degree, knowledge, and experience. The expectations here are high, so you will need to be ready for any potential interviews.

Here are some tips to help you prepare:

1. Master Core Technologies - It goes without saying that mastering your skills in certain technologies is a must for a data engineer. Python, SQL, and cloud computing platforms (AWS, Azure, or GCP) are the most sought-after skills. We have over 700 questions for interviews that can help you improve your technical skills.
2. Interview Training - Interviewing is a skill, and most people are not very adept at it simply because we don’t use it often. Certain people will have an interview only a handful of times in their lifetime. So, how exactly do you practice interviewing? Well, mock interviews are a good way to start. You can partake in it as an interviewer or interviewee to better understand how the process works and eliminate pre-interview anxiety. Our AI interviewer is another good option.
3. Prepare for the Specific Interview - All tech giants have a unique interview process, so you can’t do general prep to cover all of them. Instead, you need to get into the specifics. There is data out there for these interviews. For example, we have company interview guides that tell you exactly what to focus on during your prep.
4. Build Robust Portfolios - Create and share projects on GitHub, highlighting your ability to construct data pipelines, perform ETL processes, and manage large datasets.
5. Leverage Networking - Join professional groups, attend hackathons, and discuss on platforms like LinkedIn or Kaggle.

The landscape for data engineer jobs in 2024 is rich with opportunities. Companies like Google, Amazon, and Netflix are setting the standard in technological advancement and fostering environments where engineers thrive. Aspiring professionals should focus on building a solid foundation in data engineering principles while staying adaptable to emerging trends.

By aligning your skills with the needs of these industry leaders, you can carve out a rewarding career and contribute to the transformative power of data.