Salary for Entry-level / Junior Data Engineer during 2023
💰 The median Salary for Entry-level / Junior Data Engineer during 2023 is USD 80,000
✏️ This salary info is based on 63 individual salaries reported during 2023
Salary details
The average entry-level / junior Data Engineer salary lies between USD 60,000 and USD 125,000 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.
- Job title
- Data Engineer
- Experience
- Entry-level / Junior
- Region
- global/worldwide
- Salary year
- 2023
- Sample size
- 63
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated: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 jobsTop 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 jobsSalary Composition
The salary for an entry-level or junior data engineer typically consists of a base salary, which is the fixed component, and may include additional remuneration such as bonuses and stock options. The composition can vary significantly depending on the region, industry, and company size. In tech hubs like San Francisco or New York, the base salary might be higher due to the cost of living, while companies in smaller cities might offer a lower base but compensate with bonuses or stock options. In industries like finance or tech, bonuses can be a significant part of the compensation package, sometimes ranging from 10% to 20% of the base salary. Larger companies might offer more comprehensive benefits and stock options, whereas startups might provide equity as a part of the compensation package to attract talent.
Increasing Salary
To increase your salary from an entry-level position, consider gaining specialized skills or certifications that are in high demand. Pursuing a master's degree in data science or a related field can also enhance your qualifications. Networking within the industry and seeking mentorship can provide insights into career advancement opportunities. Additionally, gaining experience in high-demand areas such as cloud computing, big data technologies, or machine learning can make you more valuable to employers. Transitioning to a more senior role or moving to a company that offers better compensation packages are also viable strategies.
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 candidates with degrees in mathematics or statistics, provided they have relevant technical skills. A strong foundation in programming, databases, and data structures is essential. While a master's degree is not typically required for entry-level roles, it can be advantageous and may be necessary for career advancement.
Helpful Certifications
Certifications can be a great way to demonstrate your skills and commitment to the field. 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: Focuses on using AWS services for data analytics.
- Microsoft Certified: Azure Data Engineer Associate: Demonstrates expertise in integrating, transforming, and consolidating data from various structured and unstructured data systems.
These certifications can help you stand out in the job market and may lead to better job opportunities and higher salaries.
Required Experience
For entry-level data engineering roles, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant projects. Experience with programming languages such as Python, Java, or Scala, and familiarity with SQL and database management systems are often required. Knowledge of data warehousing solutions, ETL processes, and cloud platforms like AWS, Azure, or Google Cloud can also be beneficial.
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