Salary for Mid-level / Intermediate Data Engineer during 2022

Salary details

The average mid-level / intermediate Data Engineer salary lies between USD 73,880 and USD 120,000 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 Mid-level / Intermediate Data Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Data Engineer job listings are Python, Engineering and SQL. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

Python | 513 jobs Engineering | 453 jobs SQL | 451 jobs Pipelines | 415 jobs AWS | 358 jobs Data pipelines | 299 jobs ETL | 287 jobs Spark | 241 jobs Computer Science | 224 jobs Azure | 223 jobs Machine Learning | 222 jobs Big Data | 196 jobs Agile | 196 jobs Architecture | 169 jobs APIs | 169 jobs GCP | 166 jobs Airflow | 165 jobs Scala | 149 jobs Redshift | 136 jobs NoSQL | 130 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, Flex hours and Health care. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 434 jobs Flex hours | 230 jobs Health care | 229 jobs Startup environment | 182 jobs Team events | 161 jobs Competitive pay | 154 jobs Flex vacation | 120 jobs Equity / stock options | 105 jobs Parental leave | 93 jobs Salary bonus | 86 jobs Insurance | 69 jobs Medical leave | 61 jobs Gear | 44 jobs Unlimited paid time off | 43 jobs Wellness | 40 jobs Home office stipend | 40 jobs 401(k) matching | 37 jobs Conferences | 37 jobs Fitness / gym | 33 jobs Yoga | 28 jobs

Salary Composition

The salary composition for a Mid-level Data Engineer can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components:

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation. In regions with a high cost of living, such as the San Francisco Bay Area or New York City, the base salary might be higher to compensate for living expenses.

• Bonus: Bonuses can be performance-based or company-wide and are often paid annually. The bonus percentage can vary widely, ranging from 5% to 20% of the base salary, depending on the company's performance and individual contributions.

• Additional Remuneration: This includes stock options, equity, or profit-sharing plans, which are more common in tech startups or large tech companies. Benefits such as health insurance, retirement plans, and other perks also form part of the total compensation package.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in data engineering, such as cloud platforms (AWS, Azure, GCP), big data technologies (Hadoop, Spark), and data warehousing solutions (Snowflake, Redshift).

• Advanced Education: Pursuing a master's degree or specialized courses in data science, machine learning, or related fields can make you more competitive.

• Networking: Engage with professional communities, attend industry conferences, and participate in meetups to expand your network and learn about new opportunities.

• Leadership Roles: Seek opportunities to lead projects or mentor junior engineers, which can position you for promotions to senior roles.

Educational Requirements

Most mid-level data engineering positions require at least a bachelor's degree in a relevant field such as computer science, information technology, or engineering. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data systems or require advanced analytical skills.

Helpful Certifications

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

• AWS Certified Data Analytics: Validates your ability to design, build, secure, and maintain analytics solutions on AWS.

• Google Professional Data Engineer: Demonstrates proficiency in designing, building, and operationalizing data processing systems on Google Cloud Platform.

• Microsoft Certified: Azure Data Engineer Associate: Confirms your skills in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures suitable for building analytics solutions.

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, and data modeling. Familiarity with programming languages such as Python, Java, or Scala, and experience with SQL databases are also commonly required.

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