Salary for Mid-level / Intermediate Data Engineer in United States during 2022

Salary details

The average mid-level / intermediate Data Engineer salary lies between USD 95,000 and USD 160,000 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. 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, 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

In the United States, 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, bonuses, and additional remuneration such as stock options or benefits.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation package. In tech hubs like San Francisco or New York, the base salary might be higher due to the cost of living and competitive job market.

• Bonuses: These are performance-based and can vary widely. In industries like finance or tech, bonuses can be substantial, sometimes ranging from 10% to 20% of the base salary.

• Additional Remuneration: This includes stock options, profit-sharing, and other benefits like health insurance, retirement plans, and paid time off. Larger tech companies often offer stock options as a significant part of the compensation package, which can be lucrative if the company performs well.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills with the latest 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 certifications can make you more competitive and open up higher-paying opportunities.

• Networking: Engage with professional networks and communities. Attending conferences, meetups, and workshops can lead to new opportunities and insights into industry trends.

• Leadership Roles: Aim for roles that involve team leadership or project management, as these often come with higher pay.

Educational Requirements

Most mid-level Data Engineer positions require at least a bachelor's degree in a related 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

Certifications can enhance your resume and demonstrate your 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 to potential employers.

Required Experience

Typically, a mid-level Data Engineer is expected to have 3-5 years of experience in data engineering or a related field. This experience should include hands-on work with data pipelines, ETL processes, and data warehousing. Familiarity with programming languages like Python, Java, or Scala, and experience with SQL databases are also commonly required.

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