Salary for Senior-level / Expert Data Engineer during 2023

Salary details

The average senior-level / expert Data Engineer salary lies between USD 121,000 and USD 186,000 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: Nov. 17, 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 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 | 3304 jobs Engineering | 3209 jobs SQL | 3062 jobs Pipelines | 2762 jobs AWS | 2324 jobs Spark | 2201 jobs Architecture | 2187 jobs Data pipelines | 2051 jobs ETL | 1996 jobs Big Data | 1735 jobs Computer Science | 1696 jobs Agile | 1650 jobs Java | 1525 jobs Azure | 1447 jobs Airflow | 1335 jobs Kafka | 1274 jobs Machine Learning | 1263 jobs Security | 1223 jobs Scala | 1184 jobs GCP | 1177 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 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 | 2566 jobs Health care | 1375 jobs Flex hours | 1294 jobs Startup environment | 1121 jobs Team events | 915 jobs Flex vacation | 861 jobs Competitive pay | 821 jobs Equity / stock options | 780 jobs Parental leave | 706 jobs Salary bonus | 703 jobs Insurance | 688 jobs Medical leave | 506 jobs Wellness | 482 jobs 401(k) matching | 358 jobs Home office stipend | 246 jobs Fitness / gym | 195 jobs Unlimited paid time off | 184 jobs Gear | 141 jobs Conferences | 116 jobs Relocation support | 103 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 tech hubs like Silicon Valley, the base salary might be higher, but bonuses and stock options can also form a substantial part of the total compensation package. In contrast, companies in regions with a lower cost of living might offer a lower base salary but compensate with other benefits. Industries such as finance or healthcare might offer higher bonuses compared to startups, which might focus more on equity.

Increasing Salary

To increase your salary from this position, consider the following steps:

• Specialization: Develop expertise in niche areas of data engineering, such as real-time data processing or cloud data solutions, which are in high demand.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Engineering Manager or Director of Data Engineering, which typically offer higher salaries.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML and data science to remain competitive.
• Networking: Engage with professional networks and communities to explore opportunities in higher-paying industries or companies.

Educational Requirements

Most Senior-level Data Engineer positions 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, especially for roles that require a deep understanding of complex data systems and algorithms. Advanced degrees can also help in negotiating higher salaries.

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.

Required Experience

Typically, a Senior-level Data Engineer is expected to have 5-10 years of experience in data engineering or related fields. This experience should include a strong background in designing, building, and maintaining scalable data pipelines, as well as proficiency in programming languages like Python, Java, or Scala. Experience with big data technologies such as Hadoop, Spark, and Kafka is also often required.

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