Junior Data Engineer Salary at Creditsights BETA

How much does a Creditsights Junior Data Engineer make?

As of April 2025, the average annual salary for a Junior Data Engineer at Creditsights is $81,097, which translates to approximately $39 per hour. Salaries for Junior Data Engineer at Creditsights typically range from $71,195 to $95,144, reflecting the diverse roles within the company.

It's essential to understand that salaries can vary significantly based on factors such as geographic location, departmental budget, and individual qualifications. Key determinants include years of experience, specific skill sets, educational background, and relevant certifications. For a more tailored salary estimate, consider these variables when evaluating compensation for this role.

DISCLAIMER: The salary range presented here is an estimation that has been derived from our proprietary algorithm. It should be noted that this range does not originate from the company's factual payroll records or survey data.

CreditSights Overview

Website:
creditsights.com
Size:
100 - 200 Employees
Revenue:
$10M - $50M
Industry:
Business Services

Founded in 2000, CreditSights Inc is a financial research firm. The Company provides independent credit research services to institutional and corporate users in the United States and Europe. CreditSights also offers services related to issues, such as pensions, tort reforms, mergers and acquisitions, and leveraged buyouts, as well as strategic, sector, and company research services.

See similar companies related to Creditsights

What Skills Does a person Need at Creditsights?

At Creditsights, specify the abilities and skills that a person needs in order to carry out the specified job duties. Each competency has five to ten behavioral assertions that can be observed, each with a corresponding performance level (from one to five) that is required for a particular job.

  1. SQL: Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS).
  2. Python: Applying the concepts and algorithms of Python to design, develop and maintain software applications to comply with business requirements.
  3. Data engineering: Data engineering is the practice of designing and building systems for collecting, storing, and analyzing data at scale
  4. AWS: Amazon Web Services, Inc. is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis.
  5. Big Data: Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. Other concepts later attributed to big data are veracity (i.e., how much noise is in the data) and value. Current usage of the term big data tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that's not the most relevant characteristic of this new data ecosystem." Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on." Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet searches, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research.

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Check more jobs information at Creditsights

Job Title Average Creditsights Salary Hourly Rate
2 Head of Quality Assurance $285,404 $137
3 Human Resources $81,439 $39
4 Information Technology $88,663 $43
5 Manager, Commercial Operations $123,832 $60
6 President & Chief Operating Officer $524,950 $252
7 Quantitative Analyst $87,484 $42
8 Research Analyst $69,530 $33
9 Sales Development Representative $33,351 $16
10 Senior Research Analyst $79,887 $38
11 Technology Analyst $76,077 $37
12 Account Manager $86,051 $41

Hourly Pay at Creditsights

The average hourly pay at Creditsights for a Junior Data Engineer is $39 per hour. The location, department, and job description all have an impact on the typical compensation for Creditsights positions. The pay range and total remuneration for the job title are shown in the table below. Creditsights may pay a varying wage for a given position based on experience, talents, and education.
How accurate does $81,097 look to you?

FAQ about Salary and Jobs at Creditsights

1. How much does Creditsights pay per hour?
The average hourly pay is $39. The salary for each employee depends on several factors, including the level of experience, work performance, certifications and skills.
2. What is the highest salary at Creditsights?
According to the data, the highest approximate salary is about $95,144 per year. Salaries are usually determined by comparing other employees’ salaries in similar positions in the same region and industry.
3. What is the lowest pay at Creditsights?
According to the data, the lowest estimated salary is about $71,195 per year. Pay levels are mainly influenced by market forces, supply and demand, and social structures.
4. What steps can an employee take to increase their salary?
There are various ways to increase the wage. Level of education: An employee may receive a higher salary and get a promotion if they obtain advanced degrees. Experience in management: an employee with supervisory experience can increase the likelihood to earn more.