Salary for Mid-level / Intermediate Data Engineer in United States during 2023

Salary details

The average mid-level / intermediate Data Engineer salary lies between USD 102,000 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: 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, 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 for Mid-level Data Engineers

The salary for a mid-level data engineer in the United States typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company's profitability and individual performance metrics. Additional remuneration might include stock options, especially in tech companies, and comprehensive benefits packages that cover health insurance, retirement plans, and other perks.

Regional differences can affect salary composition, with tech hubs like San Francisco, New York, and Seattle offering higher base salaries and more lucrative stock options due to the higher cost of living and competitive job markets. Industry also plays a role; for instance, data engineers in finance or healthcare might receive different bonus structures compared to those in tech startups. Company size can influence the compensation package as well, with larger companies often providing more structured bonus plans and smaller companies potentially offering more 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 technical skills, especially in emerging technologies like cloud computing, big data frameworks, and machine learning. Proficiency in tools like Apache Spark, Hadoop, and cloud platforms such as AWS, Azure, or Google Cloud can make you more valuable.

• Advanced Education: Pursuing a master's degree or specialized certifications can enhance your qualifications and open up higher-paying opportunities.

• Networking and Professional Development: Attend industry conferences, join professional organizations, and engage in networking to learn about new opportunities and trends.

• Performance and Negotiation: Consistently exceed performance expectations and be prepared to negotiate your salary during performance reviews or when taking on new responsibilities.

• Transition to High-demand Sectors: Consider moving to industries with higher demand for data engineering skills, such as finance, healthcare, or tech startups.

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. A strong foundation in mathematics and statistics is also beneficial. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data modeling and analysis.

Helpful Certifications

Certifications can bolster 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 more competitive in the job market.

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

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