Data Engineer Salary in 2024

Salary details

The average Data Engineer salary lies between USD 105,000 and USD 185,000 globally. 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.

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 | 15430 jobs Python | 14868 jobs SQL | 14756 jobs Pipelines | 12872 jobs ETL | 10199 jobs Data pipelines | 9780 jobs AWS | 9707 jobs Architecture | 8904 jobs Computer Science | 8562 jobs Spark | 8436 jobs Azure | 7416 jobs Big Data | 7211 jobs Agile | 6854 jobs Security | 6671 jobs Machine Learning | 6042 jobs Java | 5586 jobs Data quality | 5581 jobs GCP | 5181 jobs Airflow | 4895 jobs Testing | 4886 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 | 11994 jobs Health care | 6281 jobs Flex hours | 5022 jobs Team events | 3681 jobs Startup environment | 3551 jobs Competitive pay | 3483 jobs Equity / stock options | 3336 jobs Flex vacation | 2756 jobs Salary bonus | 2741 jobs Insurance | 2657 jobs Parental leave | 2430 jobs Medical leave | 2181 jobs Wellness | 1723 jobs 401(k) matching | 1382 jobs Fitness / gym | 749 jobs Gear | 567 jobs Transparency | 550 jobs Home office stipend | 548 jobs Relocation support | 536 jobs Unlimited paid time off | 449 jobs

Salary Composition for Data Engineers in AI/ML/Data Science

The salary composition for a Data Engineer in AI/ML/Data Science typically includes a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. In tech hubs like Silicon Valley, bonuses and stock options can form a substantial part of the compensation, especially in larger tech companies or startups. In contrast, in regions with a lower cost of living or in smaller companies, the base salary might be more dominant, with fewer bonuses or stock options.

Steps to Increase Salary from a Data Engineer Position

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

• Skill Enhancement: Continuously update your skills with the latest technologies and tools in data engineering, such as cloud platforms (AWS, Azure, Google Cloud), big data technologies (Hadoop, Spark), and data warehousing solutions (Snowflake, Redshift).
• Advanced Education: Pursue advanced degrees or specialized courses in data science, machine learning, or related fields to enhance your expertise and marketability.
• Networking: Build a strong professional network by attending industry conferences, joining relevant online communities, and engaging with thought leaders in the field.
• Leadership Roles: Seek opportunities to lead projects or teams, which can demonstrate your capability for higher-level positions and justify a salary increase.
• Company Change: Sometimes, moving to a different company, especially one in a higher-paying industry or region, can result in a significant salary boost.

Educational Requirements for Data Engineers

Most Data Engineer positions require at least a bachelor's degree in computer science, information technology, engineering, or a related field. However, a master's degree can be advantageous and is often preferred by employers, especially for roles that involve complex data systems or integration with AI/ML projects. Courses in data structures, algorithms, database management, and software engineering are particularly relevant.

Helpful Certifications for Data Engineers

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

• Google Professional Data Engineer: Validates your ability to design, build, and operationalize data processing systems on Google Cloud Platform.
• AWS Certified Data Analytics – Specialty: Demonstrates expertise in using AWS data lakes and analytics services.
• Microsoft Certified: Azure Data Engineer Associate: Focuses on designing and implementing data management, monitoring, security, and privacy using the full stack of Azure data services.
• Cloudera Certified Professional (CCP) Data Engineer: Recognizes proficiency in data engineering skills using Cloudera's platform.

Experience Requirements for Data Engineers

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.

Related salaries

Want to contribute?