Data Engineering
Data Engineering is an area of data science that focuses on the practical application of data processing and analysis. Data engineers concentrate on big data applications and harvesting. Their function does not involve much research or experimental design. Instead, they are out where the rubber meets the road (in case of self-driving vehicles), establishing interfaces and processes for flow and access to knowledge.
RUDDERLY MENTORSHIP PROGRAM
Professionals from the industry take you under their wing. Personalised 1-1 mentorship
1 ON 1 TIME WITH SUCCESSFUL PROFESSIONALS ACROSS INDUSTRIES
IMMERSIVE MENTORSHIP STRUCTURE WITH A REAL WORLD ASSIGNMENT, TO GIVE YOU A SNEAK PEAK
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KEY SKILLS
Tools and components of data architecture
SQL
data warehousing
ETL tools
Hadoop
efficient coding
Machine learning
Knowledge of various operating systems
Building and designing large scale applications
Data modeling
Data mining
Stastical modeling
Regression analysis
Distributed Computing
Algorithms
PROS
Peaceful work environment
Good Salary
Lot of career growth opportunities
Good learning opportunities
Perfect job to utilise advanced math skills
Rapid career growth
Lot of scope of research
CONS
Time management is quite difficult
Constant interaction with the machine is tedious
Lack of some concrete knowledge about the subject
Repetitive work
OPPORTUNITY TYPES
GOT WHAT IT TAKES?
Government
Freelance
Companies
Need to be an efficient coder
Have excellent mathematical skills
Have good logical reasoning skills
have good communication skills
Know database management quite well
Should be a team player
KEY OPPORTUNITIES
Books
Podcasts
Networking Groups
Interesting Facts about the career
A data engineer is someone who prepares data for analysis. He collects data from single or multi-sources, stores these data, and does real-time or batch processing, and serves it through API. In one word, the difference between them is that data scientist only knows about data. The data engineer builds a pipeline to transform data into formats. Then a data scientist uses that format.