Data Engineer Salary in United States during 2024

Salary details

The average Data Engineer salary lies between USD 112,000 and USD 190,000 in the United States. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 15, 2024

Salary trend

Top 20 Job Tags for Data Engineer roles

The three most common job tag items assiciated with Data Engineer job listings are Engineering, Python and SQL. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Engineering | 15463 jobs Python | 14894 jobs SQL | 14788 jobs Pipelines | 12901 jobs ETL | 10221 jobs Data pipelines | 9806 jobs AWS | 9729 jobs Architecture | 8927 jobs Computer Science | 8576 jobs Spark | 8450 jobs Azure | 7433 jobs Big Data | 7223 jobs Agile | 6863 jobs Security | 6683 jobs Machine Learning | 6058 jobs Java | 5595 jobs Data quality | 5592 jobs GCP | 5191 jobs Airflow | 4907 jobs Testing | 4892 jobs

Top 20 Job Perks/Benefits for Data Engineer roles

The three most common job benefits and perks assiciated with Data Engineer job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 12013 jobs Health care | 6296 jobs Flex hours | 5034 jobs Team events | 3691 jobs Startup environment | 3553 jobs Competitive pay | 3495 jobs Equity / stock options | 3346 jobs Flex vacation | 2760 jobs Salary bonus | 2749 jobs Insurance | 2666 jobs Parental leave | 2432 jobs Medical leave | 2184 jobs Wellness | 1725 jobs 401(k) matching | 1382 jobs Fitness / gym | 750 jobs Gear | 568 jobs Transparency | 552 jobs Home office stipend | 548 jobs Relocation support | 536 jobs Unlimited paid time off | 450 jobs

Salary Composition

In the United States, the salary composition for a Data Engineer in AI/ML/Data Science typically includes a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can be a significant part of the total compensation, especially in high-growth industries.

Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market. Industry-wise, tech companies, financial services, and healthcare often offer higher salaries compared to other sectors. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and bonuses.

Increasing Salary

To increase your salary further from a Data Engineer position, consider the following steps:

• Skill Enhancement: Continuously update your technical skills, especially in emerging technologies and tools relevant to data engineering, such as cloud platforms (AWS, Azure, Google Cloud), big data technologies (Hadoop, Spark), and machine learning frameworks.

• Advanced Education: Pursuing a master’s degree or specialized certifications can make you more competitive and open up higher-paying opportunities.

• Networking: Engage with professional networks and communities to learn about new opportunities and trends in the industry.

• Leadership Roles: Aim for leadership or managerial roles, which typically come with higher salaries and additional responsibilities.

• Industry Switch: Consider moving to industries that pay higher salaries for data engineering roles, such as finance or tech.

Educational Requirements

Most Data Engineer positions require at least a bachelor’s degree in computer science, information technology, engineering, or a related field. A strong foundation in mathematics and statistics is also beneficial. Some employers may prefer candidates with a master’s degree, especially for roles that involve complex data systems or integration with AI/ML projects.

Helpful Certifications

Certifications can enhance your credentials and demonstrate expertise in specific areas. Some valuable certifications for Data Engineers include:

• Google Professional Data Engineer
• AWS Certified Data Analytics – Specialty
• Microsoft Certified: Azure Data Engineer Associate
• Cloudera Certified Professional (CCP) Data Engineer

These certifications validate your skills in cloud platforms and data engineering tools, making you a more attractive candidate to potential employers.

Experience Requirements

Typically, employers look for candidates with 3-5 years of experience in data engineering or related fields. Experience with data modeling, ETL processes, and working with large datasets is crucial. Familiarity with programming languages such as Python, Java, or Scala, and experience with SQL and NoSQL databases are often required. Experience in cloud environments and big data technologies is increasingly important.

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