Salary for Mid-level / Intermediate Data Engineer in United States during 2024

Salary details

The average mid-level / intermediate Data Engineer salary lies between USD 98,300 and USD 166,600 in the United States. 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.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). 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 | 3799 jobs SQL | 3760 jobs Python | 3685 jobs Pipelines | 3233 jobs ETL | 2752 jobs Data pipelines | 2492 jobs AWS | 2335 jobs Computer Science | 2158 jobs Architecture | 1983 jobs Spark | 1877 jobs Azure | 1847 jobs Security | 1711 jobs Agile | 1617 jobs Big Data | 1604 jobs Data quality | 1390 jobs Machine Learning | 1380 jobs Java | 1248 jobs GCP | 1189 jobs Snowflake | 1178 jobs Testing | 1173 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 | 2895 jobs Health care | 1499 jobs Flex hours | 1165 jobs Startup environment | 860 jobs Competitive pay | 859 jobs Team events | 821 jobs Equity / stock options | 723 jobs Flex vacation | 626 jobs Salary bonus | 617 jobs Parental leave | 602 jobs Insurance | 597 jobs Medical leave | 519 jobs Wellness | 412 jobs 401(k) matching | 337 jobs Fitness / gym | 161 jobs Home office stipend | 129 jobs Relocation support | 127 jobs Gear | 126 jobs Unlimited paid time off | 123 jobs Transparency | 116 jobs

Salary Composition for Mid-level Data Engineers

The salary for a mid-level data engineer in the United States typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the largest part of the total compensation package. Bonuses can vary significantly depending on the company’s performance, individual performance, and industry standards. In tech-heavy regions like Silicon Valley, bonuses and stock options might be more substantial compared to other areas. Larger companies or those in high-demand industries like finance or tech often offer more competitive bonus structures and additional perks, such as health benefits, retirement plans, and professional development opportunities.

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.
• Advanced Education: Pursue advanced degrees or specialized certifications that can set you apart from your peers.
• Networking: Build a strong professional network to learn about new opportunities and industry trends.
• Leadership Roles: Seek opportunities to lead projects or teams, which can demonstrate your capability for higher-level positions.
• Industry Transition: Consider moving to industries that offer higher compensation for data engineering roles, 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 require advanced analytical skills. A strong foundation in mathematics and statistics is also beneficial.

Helpful Certifications

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

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

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

Experience Requirements

Typically, a mid-level data engineer is expected to have 3-5 years of relevant experience. This experience should include hands-on work with data pipelines, ETL processes, data warehousing solutions, and familiarity with big data technologies like Hadoop or Spark. Experience in programming languages such as Python, Java, or Scala, and proficiency in SQL are also commonly required.

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