byGaganDeep
Updated on - 6 Aug, 2024
Post Graduate Program in Data Engineering (PGPDE) is a full-time one-year program designed to provide students with in-depth knowledge and practical skills in the area of data engineering. As at present, the PGPDE program is offered by institutes like IIIT Bangalore and Great Learning, the program covers most of the major topics in data engineering including Spark, Hadoop, SQL, NoSQL, cloud, pipelines, modeling, and warehousing.
Popular entrance exams accepted for admission into the PGPDE course are: CAT, XAT, CMAT, MAT, ATMA, GRE, and GATE are some of them, but there are other tests also. Some institutes may also have preferences based on academic achievements, relevant experience and/or personal interview rather than ranking in the entrance test. Rules for admission may differ in institute. Before applying for the program, candidates are encouraged to read more details of the admission process at the institute’s website.
| Highlights | Details |
|---|---|
| Full Form | Post Graduate Program in Data Engineering (PGPDE) |
| Duration | 1 year |
| Course Level | Postgraduate |
| Eligibility | Bachelor's degree in Engineering, Technology, Science, or related fields, minimum 50% marks |
| Top Colleges | Indian Institutes of Technology (IITs), International Institute of Information Technology (IIIT) Bangalore, Great Lakes Institute of Management, |
| Entrance Exam | GATE, institute-specific entrance exams, sometimes merit-based |
1. A degree in engineering, technology or any science related field at the first level.
2. Good critical thinking and analytical skills with focus on higher level of math and programming.
3. Convinced to become a data engineering professional and explore other careers in this area.
4. Readiness to commit time towards a rigorous program that takes one year.
5. Well defined post graduation objectives to address course concepts to real life situations.
6. Fit the specific requirements for shortlisting via the application form, essays, tests, and interviews.
| Specialization | Job Title | Average Salary (LPA) |
|---|---|---|
| Big Data Engineering | Big Data Engineer | 6 - 10+ |
| Data Warehousing & Business Intelligence (DW/BI) | Data Warehouse Engineer | 5 - 8 |
| Machine Learning Engineering | Machine Learning Engineer | 7 - 12+ |
| Data Pipelines & ETL Development | Data Pipeline Engineer | 5.5 - 9 |
| Cloud Data Engineering | Cloud Data Engineer | 6 - 10+ |