Data Engineer Salary in 2023

Salary details

The average Data Engineer salary lies between USD 110,000 and USD 180,514 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 Python, Engineering and SQL. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Python | 5352 jobs Engineering | 5125 jobs SQL | 5036 jobs Pipelines | 4382 jobs AWS | 3582 jobs Spark | 3309 jobs ETL | 3273 jobs Architecture | 3229 jobs Data pipelines | 3202 jobs Computer Science | 2748 jobs Big Data | 2603 jobs Agile | 2547 jobs Azure | 2406 jobs Java | 2258 jobs Machine Learning | 2077 jobs GCP | 1967 jobs Airflow | 1937 jobs Security | 1845 jobs Scala | 1799 jobs Kafka | 1784 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 2023 and the number of open jobs that where offering them during that period:

Career development | 4076 jobs Health care | 2146 jobs Flex hours | 2037 jobs Startup environment | 1894 jobs Team events | 1476 jobs Flex vacation | 1326 jobs Competitive pay | 1293 jobs Equity / stock options | 1110 jobs Parental leave | 1062 jobs Salary bonus | 1046 jobs Insurance | 997 jobs Medical leave | 711 jobs Wellness | 645 jobs 401(k) matching | 508 jobs Home office stipend | 375 jobs Fitness / gym | 286 jobs Gear | 275 jobs Unlimited paid time off | 265 jobs Conferences | 199 jobs Relocation support | 148 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, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Performance bonuses can vary significantly depending on the company and industry, usually accounting for 10% to 20% of the total salary. Additional remuneration, such as stock options, is more common in larger tech companies and startups, potentially making up 5% to 15% of the total compensation. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York tend to be higher due to the cost of living and demand for talent.

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 technical skills, especially in emerging technologies like cloud computing, big data frameworks, and machine learning.
• Advanced Education: Pursue advanced degrees or specialized certifications that can set you apart from your peers.
• Networking: Build a strong professional network to learn about new opportunities and industry trends.
• Leadership Roles: Aim for leadership or managerial roles that come with higher responsibilities and compensation.
• Industry Switch: Consider moving to industries that pay higher salaries for data engineering roles, such as finance or healthcare.

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 top-tier companies. Courses in data structures, algorithms, database management, and software engineering are particularly relevant. Some roles may also require knowledge of statistics and machine learning principles.

Helpful Certifications for Data Engineers

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

• Google Professional Data Engineer: Validates your ability to design, build, and operationalize data processing systems.
• 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 solutions on Microsoft Azure.
• Cloudera Certified Professional (CCP) Data Engineer: Recognizes proficiency in data engineering on the Cloudera platform.

Experience Requirements for Data Engineers

Typically, employers look for candidates with 2 to 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 big data technologies like Hadoop, Spark, or Kafka are often required.

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