As far as data-driven professions are concerned, there is an ongoing intrigue about whether data scientists hail higher salaries than data engineers or vice versa. Data scientists and data engineers have distinct positions with distinct duties and skill sets.
While data scientists are well-known for their abilities to analyze complicated data, build predictive models, and derive actionable insights, data engineers excel at designing and maintaining the infrastructure that enables data analysis.
So, let us delve into solving the intriguing quest of data engineer vs data scientist salary. We will discuss here who out-earns their data-driven professional counterparts.
Here is what we will cover:
- Factors Influencing Data Engineer and Data Scientist Salary
- Average Data Engineer Salary vs Data Scientist Salary
- Data Scientist vs Data Engineer Salary By Experience
- Data Scientist vs Data Engineer Salary By Location
- Data Engineer vs Data Scientist Salary at FAANG Companies
- Excel Your Next Data Science Interview With IK
- FAQs About Data Engineer vs Data Scientist
Factors Influencing Data Engineer and Data Scientist Salary
Comparing the salaries of data engineers and data scientists reveals that a variety of factors decide the amount of money that each professional may earn. Let us look into these influencing factors:
1. Experience and Expertise: With years of experience and a demonstrated track record of success in their respective professions, both data engineers and data scientists can see their incomes improve.
2. Location: Where one lives is an important factor in income differences. Professionals in high-tech or high-cost-of-living places tend to earn more than those in lower-cost areas.
3. Company Size: When compared to startups or smaller organizations, larger, well-established companies often provide better compensation packages.
4. Industry: The industry in which they work has a big impact on their compensation. Data specialists in banking, healthcare, and technology frequently earn better wages than those in other areas.
5. Education: A higher educational degree can lead to greater compensation in areas such as data engineering and data science.
6. Skills: Data engineers with cutting-edge technology competence and data scientists with excellent machine learning and artificial intelligence skills can receive greater compensation.
7. Professional Certifications: By demonstrating skill in specific technologies or processes, professional certifications can increase earning potential.
8. Responsibilities: The particular responsibilities and duties within every position might vary greatly, and those with more complicated or specialized work may be paid more.
9. Negotiation Skills: During the recruiting process, a candidate’s ability to negotiate a competitive compensation package might have an impact on their final salary.
10. Market Demand: The demand for data experts in a specific region or industry can have an impact on compensation. Salaries tend to be higher in locations where talent is sparse.
11. Benefits and Perks: In addition to the base income, benefits such as stock options, bonuses, remote work, and healthcare choices can all have an impact on the entire compensation package.
While data scientists and data engineers have different tasks and responsibilities, their pay is determined by a variety of interconnected factors. The intricate and developing environment of compensation in data-driven professions mandates experts to take into account a variety of elements when assessing earning potential.
Average Data Engineer Salary vs Data Scientist Salary
In the United States, both Data Engineers and Data Scientists are in great demand. The average salary for a Data Engineer in the United States is $123,110 per year, with 7.6k salaries reported as of October 24, 2023. The Data Engineer’s salary range lies between $81,988 and $184,858.
The average salary for a Data Scientist in the United States is $124,568 per year, with 5.2k salaries reported as of October 24, 2023. The Data Engineer’s salary range lies between $81,939 and $189,374.
Data Scientist vs Data Engineer Salary By Experience
Salaries paid to Data Scientist and Data Engineer differ according to the number of years of experience they have. Let us compare the salaries of Data Scientist vs Data Engineer on the basis of their years of experience in the United States.
Data Scientists
Data scientists are classified into four levels:
Level 1 – Junior Data Scientists– an entry-level position
In the US, the average income for a Junior Data Scientist is $87,658/year. The average additional cash compensation is $4,729/year. So, the average total salary for a Junior Data Scientist is $92,387/year.
Level 2 – Data Scientists– 1 to 3 years of experience
In the US, the average income for a Data Scientist is $124,315/year. The average additional cash compensation is $16,417/year. So, the average total salary for a Data Scientist is $140,732/year.
Level 3 – Senior Data Scientists– 3 to 5 years of experience
In the US, the average income for a Senior Data Scientist is $147,948/year. The average additional cash compensation is $24,447/year. So, the average total salary for a Senior Data Scientist is $172,395/year.
Level 4 – Principal Data Scientists– 10 or more years of experience
In the US, the average income for a Principal Data Scientist is $149,595/year. The average additional cash compensation is $43,901/year. So, the average total salary for a Principal Data Scientist is $193,496/year.
Note: Some levels may have sublevels depending on the industry and size of the company.
Data Engineers
A data engineer’s career path can vary depending on the size of the firm and the maturity of their data teams. However, most data engineers would likely take the following path:
Data Engineer (Junior + Mid Level)– an entry-level position
In the US, the average income for a Data Engineer (Junior + mid-level) is $75,140/year. The average additional cash compensation is $10,453/year. So, the average total salary for a Data Engineer (Junior + mid-level) is $85,592/year.
Senior Data Engineer–1 to 3 years
In the US, the average income for a Senior Data Engineer is $118,039/year. The average additional cash compensation is $16,345/year. So, the average total salary for a Senior Data Engineer is $134,384/year.
Lead & Principal Data Engineer– 4 to 6 years
The average Lead Data Engineer salary in the US is $142,819/year. The additional cash compensation is $5,000/year. The total annual salary is $147,819/year.
Senior Managerial Roles
Once data engineers have obtained around six years or more of experience, they can move into more managerial roles if they choose, such as:
Data Engineering Manager
The average salary for a Data Engineering Manager in the US is $163,516, and the average additional cash compensation is $33,978. The average total salary for a Data Engineering Manager is $197,494.
Director of Data Engineering
In the US, the average salary for a Director of Data Engineering is $237,000/year, and the average additional compensation is $32,000/year. The average total salary for a Director of Data Engineering in the US is $269,000/year.
Chief Data Officer
In the US, the average salary for a Chief Data Officer is $303,849/year, and the average additional compensation is $107,011/year. The average total salary for a Chief Data Officer is $410,864/year.
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Note: This list of roles is simplified. Organizations may expand or split roles.
Data Scientist vs Data Engineer Salary By Location
The location of a Data Scientist or Data Engineer also influences their income. Data Scientists and Data Engineers working in high-cost-of-living locations should expect to earn more than those working in smaller towns or rural areas.
Data Scientists
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Here is a list of the highest-paying cities for Data Scientists around the United States as of October 2023.
Data Engineers
Here is a list of the highest-paying cities for Data Engineers around the United States as of October 2023.
Data Engineer vs Data Scientist Salary at FAANG Companies
The responsibilities of Data Engineers and Data Scientists are extremely valuable in the fast-paced world of FAANG (Facebook, Apple, Amazon, Netflix, and Google) tech titans. These data-driven experts are the foundation of data-driven innovation, and their compensation reflects their critical contributions to the latest technologies and decision-making processes.
The table below shows a comparison of the average Data Engineer vs Data Scientist salary offered by FAANG companies.
Excel Your Next Data Science Interview With IK
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FAQs About Data Engineer vs Data Scientist
1. What is a data analyst vs data scientist salary?
When we discuss data scientist vs data analyst salary, we need to know that data scientists earn more. Data scientists typically have a greater educational background and more responsibility in front-end development. Salaries for data analysts and data scientists might vary depending on geographical location, seniority, sector, and skill set.
2. Does a Data Engineer code?
Data engineers need coding skills, and Python, along with SQL and other programming languages, is a popular choice for numerous tasks, making it an essential skill in data science professions.
3. Does a Data Engineer need a Ph.D.?
A Ph.D. is not often necessary for careers in data engineering. Because data engineering is less academically focused than data science, many data engineers excel with good design and programming skill sets but no graduate degree.
4. Can I move from Data Engineer to Data Scientist?
Such interchange is not guaranteed. However, a new generation of engineers is merging data science and data engineering skills, breaking the conventional divide between the two roles.
5. Can a Data Analyst become a Data Engineer?
Individuals with sufficient experience and extra training may opt for a move from the role of data analyst to that of data engineer.
