Data Engineer – promising prospects in Big Data Management
The task of a Data Engineer is to collect, process and review data as an essential basis for big data, data warehouse and analysis projects. Data Engineers are essential employees in modern, data-driven companies.
It is an important area to make the best use of so-called big data. They play an essential role in the advancement of the corporate objectives and the success of the company. Likewise, a Data Engineer constantly improves the existing databases and the algorithmus used, thus constantly developing the analysis of the data.
Prerequisites for the profession are a technical interest, basic knowledge of programming, insight into data processing, and an understanding of data processes.
With increasing digitalisation, the need for employees familiar with IT, data, data security and the technical processing of data and its constant optimisation is also growing. In this regard, the career opportunities for a Data Engineer are very high.
Your tasks in the company upon successful completion:
A Data Engineer creates the link between hardware and data processing by monitoring data sources and preparing the existing data, not only to manage it but to prepare it for analysis and interpretation.
An empathetic personality and social skills also play a role in the job profile. This is because a data engineer has contact with employees from other departments within the company, to whom facts about data and its analysis and conclusions, which are often perceived as complex by laypersons, have to be explained.
Why are Data Engineers in high demand?
The training opportunities are lagging the great demand. The typical Data Engineer is usually a job or career changer. This is exactly why we offer this exciting bootcamp.
The job market for Data Engineers is excellent. The demand is so high that specialists generally have a background in other fields such as computer science, business informatics, statistics, or other computer-related activities.
Many have self-taught know-how through "learning by doing". This is changing now with our bootcamp Data Engineer.
Working environment
The digitalization of businesses is rapidly progressing, and with it, the need to administer, manage, improve, and ultimately process the generated and collected data for use by the company. Professionals with the relevant knowledge are in great demand.
The great thing is that the job can also be done remotely from anywhere in the world. Employers focus primarily on the result and not necessarily on the number of hours worked.
Visualize being in an Airbnb in Italy, working on your new project for a German company. Your morning starts with a walk in the mountain. During the day, you use the time for team meetings and client communication – and you finish your day with a glass of wine on your terrace!
Just a dream? Your future starts here if you choose the bootcamp Data Engineer.
Lesson times are monday to friday from 9 am to 6 pm (GMT)
Learning Content
Week | Data Engineer |
---|---|
1 | General understanding of technology |
2 | Phython |
3 | Phython |
4 | Phython |
5 | Databases, models and visualizations |
6 | Databases, models and visualizations |
7 | Databases, models and visualizations |
8 | Softskills |
9 | Softskills |
10 | Sustainability in IT |
11 | Exercise phases and Project |
12 | Exercise phases and Project |
Start Now!
Next starting date: 20.02.2023 (GMT) BOOK Now
Next starting date: 20.02.2023 (GMT) BOOK Now
More Details
Become a Data Engineer
Length, content, schedule
Length of the course: 60 days with 9 teaching units (TU) = 540 TU
Full Data Analyst Course |
Teaching Units (TU) |
Week 1-12 |
|
General technological understanding |
45 |
Python |
144 |
Databases, models and visualisation |
135 |
Advanced skills |
36 |
Green IT |
27 |
Exercises |
54 |
Final project |
99 |
Sum of teaching units |
540 |
Course objectives
In this course, participants receive practical training and user-related skills in the field of the Data Engineer. Data Engineers develop and optimise the systems that enable Data Scientists and Data Analysts to perform their tasks and work. The course presents a variety of content and competencies needed to meet the professional requirements of a Data Engineer.
Target group
This course is aimed in particular at qualified professionals who do not yet have any experience with programming or the Python programming language.
Prerequisites / Level of assistance
You should possess basic IT skills – such as the use of Office products and the internet. Furthermore, participants should be proficient in the language used in the course (English).
Methodical-didactical concept
The following modules form the basis of the knowledge transfer:
- Practical classes with lecturer
- Exercises accompanying the lessons (independent learning)
- Team-oriented group work
- Practical examples and exercises
- Learning assessments
- Virtual face-to-face teaching via Teams or similar VC (Virtual Classroom). Participants: work on two screens and can see the trainer at all times and communicate directly with him/her via voice or chat
Employment support and cooperation with employers
The training is accompanied by job application support measures. Greenbootcamps has a network of companies that are looking for employees with the Data Analyst qualification.
These cooperation partners are involved in the application process from the beginning and accompany the participants during the bootcamps. Upon successful completion, they are guaranteed a permanent position.
Learning assessments
Within the course, corresponding learning assessments are planned (at the end of each section). Within the lessons, exercises conclude individual learning units.
Certificate
Upon successful completion, the participant will receive an internationally valid certificate from Greenbootcamps as well as an evaluation of their performance. Furthermore, you will receive a certificate as ITIL® 4 Specialist: Sustainability In Digital & IT.
Learning and teaching aids
Participants work with digital learning materials that they can download via the learning management system. The learning management system is online and is available to all participants during the training.
Required software
MS Office, internet access, additional open source applications (such as MS Power BI Desktop, Hadoop, Anaconda), learning management system, online communication system.