The average pay for a Data Engineer with Python skills is C$30.00 per hour.
The average pay for a Data Engineer with Python skills is C$72,490 per year.
|Salary||C$54,534 - C$94,189|
|Bonus||C$4,949 - C$13,404|
|Total Pay (|
XTotal Pay combines base annual salary or hourly wage, bonuses, profit sharing, tips, commissions, overtime pay and other forms of cash earnings, as applicable for this job. It does not include equity (stock) compensation, cash value of retirement benefits, or the value of other non-cash benefits (e.g. healthcare).)
|C$54,962 - C$102,514|
Job Description for Data Engineer
Data engineers typically work in an indoor office setting, and a college degree in computer science, engineering, or a related field is often a minimum requirement for this position. Computer skills, particularly with Linux systems, and three to five years of prior work experience may also be required, and applicants should have knowledge of algorithms, data structures, and performance optimism and experience with processing and interpreting data sets.Read More...
Data engineers are responsible for developing and translating computer algorithms into prototype code and maintaining, organizing, and identifying trends in large data sets. Expected skills and experience also include proficiency in SQL database design, proficiency in creating process documentation, strong written and verbal communication skills, and the ability to work independently and on teams. Familiarity with the computer coding languages python, java, kafka, hive, or storm may be required in order to oversee real-time business metric aggregation, data warehousing and querying, schema and data management, and related duties.
Data engineers often work on teams and should enjoy working with other data engineers. Work schedules are often flexible and offer the possibilities of working from home, paid days off, 401k, vacation time, and health insurance. (Copyright 2019 PayScale.com)
- Develop technical solutions to improve access to data and data usage.
- Understand data needs and advise company on technological resources.
- Aggregate and analyze various data sets to provide actionable insight.
- Develop reports, dashboards, and tools for business-users.
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