Salary for Mid-level / Intermediate Data Engineer during 2024

Salary details

The average mid-level / intermediate Data Engineer salary lies between USD 90,000 and USD 160,000 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 Mid-level / Intermediate Data Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Data Engineer job listings are Engineering, SQL and Python. 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 | 3790 jobs SQL | 3749 jobs Python | 3675 jobs Pipelines | 3224 jobs ETL | 2744 jobs Data pipelines | 2484 jobs AWS | 2328 jobs Computer Science | 2154 jobs Architecture | 1975 jobs Spark | 1873 jobs Azure | 1840 jobs Security | 1707 jobs Agile | 1612 jobs Big Data | 1603 jobs Data quality | 1383 jobs Machine Learning | 1378 jobs Java | 1244 jobs GCP | 1185 jobs Testing | 1170 jobs Snowflake | 1169 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 2024 and the number of open jobs that where offering them during that period:

Career development | 2893 jobs Health care | 1498 jobs Flex hours | 1162 jobs Startup environment | 860 jobs Competitive pay | 858 jobs Team events | 817 jobs Equity / stock options | 722 jobs Flex vacation | 626 jobs Salary bonus | 615 jobs Parental leave | 602 jobs Insurance | 596 jobs Medical leave | 519 jobs Wellness | 412 jobs 401(k) matching | 337 jobs Fitness / gym | 161 jobs Home office stipend | 129 jobs Gear | 126 jobs Relocation support | 126 jobs Unlimited paid time off | 123 jobs Transparency | 116 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. Performance bonuses can vary significantly depending on the company's performance and individual achievements, 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. The composition can vary by region, with tech hubs like Silicon Valley offering higher base salaries and stock options, while other regions might offer more balanced packages. Industry and company size also play a role; larger companies might offer more comprehensive benefits, while startups might compensate with equity.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools relevant to data engineering, such as cloud platforms (AWS, Azure, GCP), big data technologies (Hadoop, Spark), and machine learning frameworks.
• Advanced Education: Pursue advanced degrees or specialized courses in data science, machine learning, or related fields to enhance your expertise and marketability.
• Certifications: Obtain relevant certifications that demonstrate your proficiency and commitment to the field.
• Networking: Engage with professional networks and communities to learn about new opportunities and trends.
• Leadership Roles: Seek opportunities to lead projects or teams, which can position you for promotions and salary increases.
• Industry Transition: Consider transitioning to industries with higher pay scales for data engineers, such as finance or tech.

Educational Requirements

Most Mid-level Data Engineer 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 machine learning applications. A strong foundation in mathematics, statistics, and programming is essential, as these skills are critical for 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
• AWS Certified Data Analytics – Specialty
• Microsoft Certified: Azure Data Engineer Associate
• Cloudera Certified Professional (CCP) Data Engineer
• IBM Data Engineering Professional Certificate

These certifications validate your skills in data engineering tools and platforms, making you a more competitive candidate.

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 such as Python, Java, or Scala. Experience with cloud platforms and big data technologies is also highly valued.

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