Salary for Entry-level / Junior Data Engineer in United States during 2023

Salary details

The average entry-level / junior Data Engineer salary lies between USD 65,000 and USD 130,002 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. 10, 2024

Salary trend

Top 20 Job Tags for Entry-level / Junior Data Engineer roles

The three most common job tag items assiciated with entry-level / junior 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 | 595 jobs SQL | 546 jobs Engineering | 450 jobs Pipelines | 353 jobs ETL | 342 jobs AWS | 301 jobs Spark | 291 jobs Big Data | 261 jobs Architecture | 253 jobs GCP | 241 jobs Computer Science | 235 jobs Azure | 234 jobs Machine Learning | 226 jobs Data pipelines | 214 jobs Java | 204 jobs DevOps | 183 jobs Agile | 173 jobs NoSQL | 168 jobs APIs | 164 jobs Docker | 146 jobs

Top 20 Job Perks/Benefits for Entry-level / Junior Data Engineer roles

The three most common job benefits and perks assiciated with entry-level / junior Data Engineer job listings are Career development, Startup environment 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 | 329 jobs Startup environment | 192 jobs Flex hours | 142 jobs Team events | 113 jobs Health care | 112 jobs Flex vacation | 91 jobs Competitive pay | 90 jobs Salary bonus | 72 jobs Equity / stock options | 59 jobs Insurance | 57 jobs Parental leave | 56 jobs Yoga | 31 jobs Medical leave | 31 jobs 401(k) matching | 23 jobs Wellness | 23 jobs Snacks / Drinks | 20 jobs Home office stipend | 18 jobs Gear | 17 jobs Conferences | 16 jobs Fitness / gym | 14 jobs

Salary Composition

The salary for an entry-level or junior data engineer in the United States typically consists of a base salary, which is the fixed amount, and may include additional components such as bonuses and other forms of remuneration. The base salary is often the largest portion, making up the majority of the total compensation package. Bonuses can vary significantly depending on the company and industry. For instance, tech companies or startups might offer performance-based bonuses or stock options, while larger, more established firms might provide annual bonuses based on company performance. Additionally, benefits such as health insurance, retirement contributions, and paid time off can add significant value to the overall compensation package. The region also plays a crucial role; for example, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market.

Steps to Increase Salary

To increase your salary from an entry-level position, consider the following strategies:

• Skill Enhancement: Continuously upgrade your technical skills, especially in emerging technologies and tools relevant to data engineering.
• Advanced Education: Pursuing a master's degree or specialized courses in data science or engineering can make you more competitive.
• Certifications: Obtain relevant certifications that demonstrate your expertise and commitment to the field.
• Networking: Build a strong professional network to learn about new opportunities and industry trends.
• Performance Excellence: Consistently exceed performance expectations to position yourself for promotions and raises.
• Industry Transition: Consider moving to industries that pay higher salaries for data engineering roles, such as finance or healthcare.

Educational Requirements

Most entry-level data engineering positions require at least a bachelor's degree in a related field such as computer science, information technology, engineering, or mathematics. Some employers may also consider candidates with degrees in other quantitative fields if they have relevant skills and experience. A strong foundation in programming, databases, and data structures is essential. Additionally, coursework or projects in data analytics, machine learning, or big data technologies can be advantageous.

Helpful Certifications

While not always mandatory, certain certifications can enhance your resume and demonstrate your expertise to potential employers. Some valuable certifications include:

• AWS Certified Data Analytics – Specialty
• Google Professional Data Engineer
• Microsoft Certified: Azure Data Engineer Associate
• Cloudera Certified Professional (CCP) Data Engineer

These certifications validate your skills in specific platforms and tools, making you more attractive to employers who use these technologies.

Required Experience

For entry-level positions, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant projects during your studies. Experience with data processing frameworks like Apache Hadoop or Spark, as well as proficiency in SQL and programming languages such as Python or Java, is often expected. Familiarity with cloud platforms like AWS, Google Cloud, or Azure can also be beneficial.

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