Salary for Senior-level / Expert Data Engineer in United States during 2022

Salary details

The average senior-level / expert Data Engineer salary lies between USD 120,000 and USD 182,500 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. 10, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Data Engineer roles

The three most common job tag items assiciated with senior-level / expert 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 | 2120 jobs Python | 2044 jobs SQL | 1883 jobs Pipelines | 1869 jobs AWS | 1535 jobs Data pipelines | 1393 jobs Spark | 1327 jobs ETL | 1270 jobs Big Data | 1043 jobs Airflow | 992 jobs Computer Science | 967 jobs Machine Learning | 903 jobs Agile | 861 jobs Kafka | 820 jobs Streaming | 798 jobs Architecture | 777 jobs Redshift | 767 jobs Scala | 755 jobs GCP | 694 jobs Snowflake | 688 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert 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 | 1608 jobs Health care | 902 jobs Startup environment | 831 jobs Flex hours | 723 jobs Flex vacation | 640 jobs Team events | 630 jobs Equity / stock options | 593 jobs Competitive pay | 545 jobs Insurance | 444 jobs Parental leave | 439 jobs Medical leave | 329 jobs Salary bonus | 309 jobs Wellness | 279 jobs 401(k) matching | 255 jobs Home office stipend | 209 jobs Unlimited paid time off | 207 jobs Fitness / gym | 175 jobs Conferences | 147 jobs Snacks / Drinks | 99 jobs Travel | 68 jobs

Salary Composition for Senior Data Engineers

In the United States, the salary for a Senior Data Engineer typically comprises 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, often between 10% to 20% of the total compensation, depending on the company's performance and individual contributions. Additional remuneration, such as stock options, is more prevalent in larger tech companies and startups, where it can form a significant part of the compensation package. The composition can also vary by region, with tech hubs like San Francisco and New York offering higher base salaries and more substantial equity components compared to other regions.

Steps to Increase Salary

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

• Specialize in High-Demand Skills: Acquiring expertise in emerging technologies such as machine learning, artificial intelligence, or cloud computing can make you more valuable.
• Pursue Leadership Roles: Transitioning into roles like Data Engineering Manager or Director of Data Engineering can lead to higher compensation.
• Negotiate Effectively: When changing jobs or during performance reviews, negotiate for higher pay by demonstrating your impact and market value.
• Expand Your Network: Engage with industry professionals through conferences, meetups, and online platforms to learn about new opportunities.
• Consider Relocation: Moving to a region with a higher cost of living, like Silicon Valley, can result in a higher salary.

Educational Requirements

Most Senior Data Engineer roles require at least a bachelor's degree in computer science, information technology, engineering, or a related field. However, a master's degree or even a Ph.D. can be advantageous, particularly for roles that involve complex data modeling or machine learning. Advanced degrees can also provide a competitive edge in the job market and may lead to higher starting salaries.

Helpful Certifications

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

• AWS Certified Big Data – Specialty: Validates your skills in using AWS data services.
• Google Professional Data Engineer: Demonstrates your ability to design, build, and operationalize data processing systems.
• Microsoft Certified: Azure Data Engineer Associate: Focuses on implementing data solutions using Azure services.
• Cloudera Certified Professional (CCP) Data Engineer: Recognizes proficiency in data engineering on the Cloudera platform.

Experience Requirements

Typically, a Senior Data Engineer position requires 5 to 10 years of experience in data engineering or related fields. This experience should include a strong background in data architecture, ETL processes, data warehousing, and proficiency in programming languages such as Python, Java, or Scala. Experience with big data technologies like Hadoop, Spark, and Kafka is also highly valued.

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