Data Engineer Salary in United States during 2022

Salary details

The average Data Engineer salary lies between USD 117,000 and USD 180,000 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. 22, 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 2022 and the number of open jobs that where associated with them during that period:

Engineering | 3182 jobs Python | 3142 jobs SQL | 2848 jobs Pipelines | 2738 jobs AWS | 2250 jobs Data pipelines | 1996 jobs ETL | 1894 jobs Spark | 1856 jobs Big Data | 1479 jobs Computer Science | 1438 jobs Machine Learning | 1387 jobs Airflow | 1371 jobs Agile | 1291 jobs Scala | 1103 jobs Kafka | 1100 jobs Architecture | 1090 jobs GCP | 1051 jobs Redshift | 1036 jobs Streaming | 1036 jobs Azure | 999 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 Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 2509 jobs Health care | 1352 jobs Startup environment | 1217 jobs Flex hours | 1171 jobs Team events | 961 jobs Flex vacation | 913 jobs Competitive pay | 839 jobs Equity / stock options | 811 jobs Parental leave | 620 jobs Insurance | 609 jobs Salary bonus | 489 jobs Medical leave | 481 jobs Wellness | 369 jobs 401(k) matching | 342 jobs Home office stipend | 293 jobs Unlimited paid time off | 283 jobs Fitness / gym | 237 jobs Conferences | 225 jobs Gear | 136 jobs Snacks / Drinks | 131 jobs

Salary Composition

In the United States, the salary composition for a Data Engineer can vary significantly based on factors such as region, industry, and company size. Typically, the salary package is divided into three main components:

• Base Salary: This is the fixed annual salary and usually constitutes the largest portion of the total compensation. In tech hubs like San Francisco or New York, the base salary might be higher due to the cost of living and competitive job market.

• Bonus: Many companies offer annual performance bonuses, which can range from 5% to 20% of the base salary. The bonus structure often depends on individual performance, company performance, or a combination of both.

• Additional Remuneration: This can include stock options, restricted stock units (RSUs), or other equity compensation, especially in tech companies and startups. Benefits such as health insurance, retirement plans, and other perks also contribute to the overall compensation package.

Increasing Salary

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, GCP), 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. Attending conferences, meetups, and workshops can lead to new opportunities and insights into higher-paying roles.

• Negotiation: When offered a new position or during performance reviews, negotiate your salary and benefits package. Research industry standards to make informed requests.

Educational Requirements

Most Data Engineer positions require at least a bachelor's degree in a related field such as Computer Science, Information Technology, or Engineering. Some employers may prefer candidates with a master's degree, especially for senior roles. Coursework in data structures, algorithms, database management, and software engineering is highly beneficial.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

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

These certifications validate your skills in specific platforms and tools, making you more attractive to potential employers.

Experience Requirements

Typically, a Data Engineer role requires 2-5 years of experience in data management, software development, or a related field. Experience with data modeling, ETL processes, and working with large datasets is often essential. For senior positions, 5-10 years of experience may be required, along with leadership or project management experience.

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