Salary for Senior-level / Expert Data Engineer during 2022

Salary details

The average senior-level / expert Data Engineer salary lies between USD 115,000 and USD 180,000 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 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

The salary for a Senior-level or Expert Data Engineer typically comprises a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The composition can vary significantly depending on the region, industry, and company size. In the United States, for instance, tech hubs like San Francisco or New York may offer higher base salaries and more substantial equity packages compared to other regions. In industries like finance or healthcare, bonuses might be more prevalent, reflecting the industry's profitability and performance metrics. Smaller startups might offer lower base salaries but compensate with significant equity stakes, while larger corporations might provide a more balanced mix of salary and bonuses.

Increasing Salary

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

• Specialize in Niche Areas: Developing expertise in high-demand areas such as machine learning engineering, big data technologies, 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 Equity and Bonuses: If you're in a position to negotiate, focus on increasing your equity stake or performance bonuses.
• Switch Industries or Companies: Sometimes, moving to a different industry or a company known for higher pay scales can result in a significant salary increase.

Educational Requirements

Most Senior-level Data Engineer positions require at least a bachelor's degree in computer science, information technology, or a related field. However, a master's degree or even a Ph.D. can be advantageous, especially for roles that require a deep understanding of complex data systems and algorithms. Advanced degrees can also help in securing higher-level positions and salaries.

Helpful Certifications

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

• Certified Data Management Professional (CDMP)
• Google Professional Data Engineer
• AWS Certified Big Data – Specialty
• Microsoft Certified: Azure Data Engineer Associate

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

Required Experience

Typically, a Senior-level Data Engineer is expected to have at least 5-10 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 cloud platforms (AWS, Azure, Google Cloud) is also highly valued.

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