Data Engineer Salary in United States during 2023

Salary details

The average Data Engineer salary lies between USD 115,830 and USD 184,800 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: Nov. 17, 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 for a Data Engineer in the AI/ML/Data Science field typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the largest part 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 might be more substantial compared to other regions. Additional remuneration often includes stock options, especially in tech companies, which can be a significant part of the compensation in startups or large tech firms. Benefits such as health insurance, retirement plans, and paid time off also contribute to the overall package. The composition can vary based on the region, with higher salaries typically found in major tech cities, and by company size, with larger companies often offering more comprehensive packages.

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: 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.

• Performance and Negotiation: Consistently perform well in your current role and be prepared to negotiate your salary during performance reviews or when offered a new position.

• Transition to High-Demand Roles: Consider transitioning to roles that are in higher demand or have a higher salary potential, such as Data Architect or Machine Learning Engineer.

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. A strong foundation in mathematics and statistics is also beneficial. Some positions, especially those in more competitive markets or at leading tech companies, may require a master's degree or higher. Relevant coursework or experience in database management, data structures, and algorithms is often essential.

Helpful Certifications for Data Engineers

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

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

These certifications validate your skills in cloud platforms and big data technologies, which are crucial for data engineering roles.

Experience Requirements for Data Engineers

Typically, Data Engineer roles require 2-5 years of experience in data management, software engineering, or a related field. Experience with data modeling, ETL processes, and working with large datasets is often necessary. Familiarity with programming languages such as Python, Java, or Scala, and experience with SQL and NoSQL databases are also commonly required.

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