Salary for Senior-level / Expert Data Engineer during 2024
💰 The median Salary for Senior-level / Expert Data Engineer during 2024 is USD 155,000
✏️ This salary info is based on 4016 individual salaries reported during 2024
Salary details
The average senior-level / expert Data Engineer salary lies between USD 119,000 and USD 196,747 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.
- Job title
- Data Engineer
- Experience
- Senior-level / Expert
- Region
- global/worldwide
- Salary year
- 2024
- Sample size
- 4016
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated: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 2024 and the number of open jobs that where associated with them during that period:
Engineering | 8999 jobs Python | 8544 jobs SQL | 8376 jobs Pipelines | 7595 jobs AWS | 5975 jobs Data pipelines | 5863 jobs ETL | 5729 jobs Architecture | 5672 jobs Spark | 5368 jobs Computer Science | 4864 jobs Big Data | 4395 jobs Azure | 4333 jobs Agile | 4154 jobs Security | 3938 jobs Machine Learning | 3665 jobs Java | 3420 jobs Data quality | 3364 jobs Airflow | 3196 jobs GCP | 3191 jobs Snowflake | 3083 jobsTop 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 Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:
Career development | 6983 jobs Health care | 3785 jobs Flex hours | 2970 jobs Team events | 2239 jobs Competitive pay | 2122 jobs Startup environment | 2109 jobs Equity / stock options | 2006 jobs Salary bonus | 1719 jobs Flex vacation | 1701 jobs Insurance | 1567 jobs Parental leave | 1469 jobs Medical leave | 1273 jobs Wellness | 1046 jobs 401(k) matching | 841 jobs Fitness / gym | 421 jobs Gear | 380 jobs Home office stipend | 350 jobs Transparency | 346 jobs Conferences | 294 jobs Relocation support | 292 jobsSalary Composition
The salary for a Senior-level or Expert Data Engineer in AI/ML/Data Science typically comprises several components. The fixed base salary is the largest portion, often accounting for 70-80% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually make up 10-20% of the total salary. Additional remuneration might include stock options, especially in tech companies, and other benefits such as health insurance, retirement contributions, and paid time off. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech giants in Silicon Valley might offer substantial stock options, while companies in other regions might focus more on cash bonuses.
Increasing Salary Further
To increase your salary beyond the median of USD 155,000, consider pursuing leadership roles such as Data Engineering Manager or Director of Data Engineering. These positions not only offer higher salaries but also provide opportunities to influence strategic decisions. Additionally, specializing in high-demand areas like cloud computing, big data technologies, or machine learning can make you more valuable. Networking within industry circles and attending conferences can also open doors to higher-paying opportunities. Lastly, consider negotiating your salary by leveraging offers from other companies or highlighting your contributions and achievements in your current role.
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 in competitive markets or for roles that require a deep understanding of machine learning and data science principles. Advanced degrees can also provide a more comprehensive understanding of complex data systems and algorithms, which are crucial for high-level data engineering tasks.
Helpful Certifications
Certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications for data engineers include:
- Google Professional Data Engineer: Validates your ability to design, build, and operationalize data processing systems.
- AWS Certified Big Data – Specialty: Focuses on big data solutions on the AWS platform.
- Microsoft Certified: Azure Data Engineer Associate: Demonstrates your skills in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions.
These certifications can help you stand out in the job market and may lead to higher salary offers.
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, and data warehousing. Experience with cloud platforms like AWS, Azure, or Google Cloud is often required, as is proficiency in programming languages such as Python, Java, or Scala. Experience in leading projects or teams can also be beneficial, as it demonstrates your ability to manage complex data engineering tasks and collaborate effectively with other departments.
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