Salary for Entry-level / Junior Data Engineer in United States during 2022

Salary details

The average entry-level / junior Data Engineer salary lies between USD 86,000 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 Entry-level / Junior Data Engineer roles

The three most common job tag items assiciated with entry-level / junior 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 | 196 jobs Engineering | 187 jobs SQL | 166 jobs Pipelines | 118 jobs ETL | 102 jobs AWS | 102 jobs Computer Science | 84 jobs Data pipelines | 82 jobs Machine Learning | 72 jobs Big Data | 70 jobs Spark | 70 jobs Airflow | 59 jobs GCP | 56 jobs APIs | 54 jobs Azure | 52 jobs Scala | 50 jobs Agile | 47 jobs Testing | 46 jobs Research | 42 jobs Architecture | 39 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 Team events. 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 | 121 jobs Startup environment | 62 jobs Team events | 60 jobs Flex hours | 59 jobs Health care | 49 jobs Competitive pay | 35 jobs Flex vacation | 34 jobs Equity / stock options | 24 jobs Salary bonus | 23 jobs Parental leave | 18 jobs Insurance | 15 jobs Medical leave | 14 jobs Wellness | 13 jobs Home office stipend | 12 jobs 401(k) matching | 11 jobs Fitness / gym | 9 jobs Unlimited paid time off | 9 jobs Lunch / meals | 8 jobs Snacks / Drinks | 7 jobs Conferences | 6 jobs

Salary Composition

The salary for an entry-level or junior data engineer in the United States typically consists of a base salary, performance bonuses, and sometimes additional remuneration such as stock options or benefits. The base salary is the fixed component and usually makes up the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and the individual's performance. Additional remuneration might include stock options, especially in tech companies, or other benefits like health insurance, retirement plans, and paid time off. The composition can vary by region, with tech hubs like San Francisco or New York offering higher base salaries but potentially less in bonuses due to the high cost of living. Industry also plays a role; for instance, finance and tech industries might offer more lucrative packages compared to non-profit sectors. Company size can influence the package as well, with larger companies often providing more comprehensive benefits and bonuses.

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: Pursue further education, such as a master's degree in data science or a related field, which can open up higher-paying opportunities.
• Certifications: Obtain relevant certifications that can validate your skills and make you more competitive.
• Networking: Build a strong professional network to learn about new opportunities and gain insights into industry trends.
• Performance Excellence: Consistently exceed performance expectations to position yourself for promotions and salary increases.
• Industry Switch: Consider moving to a higher-paying industry or a region with a higher cost of living, which often correlates with higher salaries.

Educational Requirements

Most entry-level data engineering positions require at least a bachelor's degree in computer science, information technology, engineering, or a related field. Some employers may accept degrees in mathematics or statistics if the candidate has relevant technical skills. A strong foundation in programming, databases, and data structures is essential. While a bachelor's degree is often sufficient for entry-level roles, a master's degree can be advantageous and may be required for more advanced positions.

Helpful Certifications

Certifications can be a valuable addition to your resume, demonstrating your commitment to the field and your expertise in specific areas. Some common and helpful certifications for data engineers include:

• Google Professional Data Engineer: Validates your ability to design, build, and operationalize data processing systems.
• AWS Certified Data Analytics – Specialty: Demonstrates expertise in using AWS data lakes and analytics services.
• Microsoft Certified: Azure Data Engineer Associate: Focuses on designing and implementing data solutions on Microsoft Azure.
• Cloudera Certified Professional (CCP) Data Engineer: Recognizes proficiency in data engineering on the Cloudera platform.

Experience Requirements

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, such as Apache Hadoop or Spark, and familiarity with SQL and NoSQL databases are often required. While extensive professional experience is not necessary for entry-level roles, demonstrating hands-on experience with data engineering tools and technologies can be beneficial.

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