Salary for Mid-level / Intermediate Data Engineer during 2023

Salary details

The average mid-level / intermediate Data Engineer salary lies between USD 90,000 and USD 151,410 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. 22, 2024

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Data Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Data Engineer job listings are Python, SQL and Engineering. 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 | 1005 jobs SQL | 983 jobs Engineering | 967 jobs Pipelines | 885 jobs AWS | 673 jobs Data pipelines | 673 jobs ETL | 638 jobs Computer Science | 565 jobs Architecture | 527 jobs Spark | 520 jobs Azure | 508 jobs Agile | 449 jobs Machine Learning | 385 jobs GCP | 363 jobs Big Data | 359 jobs Security | 339 jobs Data quality | 329 jobs Airflow | 324 jobs Data warehouse | 311 jobs Java | 311 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate 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 | 779 jobs Health care | 462 jobs Flex hours | 416 jobs Startup environment | 374 jobs Team events | 302 jobs Competitive pay | 274 jobs Flex vacation | 260 jobs Parental leave | 217 jobs Equity / stock options | 166 jobs Salary bonus | 161 jobs Insurance | 153 jobs Medical leave | 109 jobs Wellness | 93 jobs 401(k) matching | 92 jobs Home office stipend | 79 jobs Gear | 78 jobs Conferences | 52 jobs Unlimited paid time off | 51 jobs Fitness / gym | 50 jobs Yoga | 32 jobs

Salary Composition

The salary for a Mid-level Data Engineer in AI/ML/Data Science typically consists of a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually makes up the majority of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration might include stock options, especially in tech companies or startups, and benefits like health insurance, retirement contributions, and paid time off.

Regional differences can also impact salary composition. For instance, tech hubs like San Francisco or New York may offer higher base salaries and more substantial stock options due to the higher cost of living and competitive job market. Industry-wise, tech companies and financial services often provide more lucrative compensation packages compared to other sectors. Company size can also play a role; larger companies might offer more comprehensive benefits, while startups might compensate with equity options.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your technical skills, especially in emerging technologies and tools relevant to data engineering, such as cloud platforms, big data technologies, and machine learning frameworks.
• 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 to learn about new opportunities and trends in the industry.
• Leadership Roles: Aim for roles that involve team leadership or project management, as these often come with higher compensation.
• Industry Switch: Consider moving to industries that pay more for data engineering skills, such as finance or tech.

Educational Requirements

Most mid-level data engineering positions require at least a bachelor's degree in computer science, information technology, engineering, or a related field. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data systems or integration with AI/ML projects. A strong foundation in mathematics and statistics is also beneficial, given the analytical nature of the work.

Helpful Certifications

Certifications can enhance your credentials and demonstrate expertise in specific areas. Some valuable certifications for data engineers include:

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

These certifications validate your skills in cloud platforms and data engineering tools, making you a more attractive candidate for employers.

Required Experience

Typically, a mid-level data engineer is expected to have 3-5 years of experience in data engineering or related fields. This experience should include hands-on work with data pipelines, ETL processes, data warehousing, and familiarity with programming languages like Python, Java, or Scala. Experience with cloud platforms (AWS, Azure, Google Cloud) and big data technologies (Hadoop, Spark) is often required.

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