Big Data Engineering

Big Data Engineering Program: Meet the Big Demand for Big Data

What is the relevance of Big Data?

The world around us is changing but what is constant is the magnitude of data it is generating. With technology reshaping every sphere of our lives, data becomes the backbone to ensure its smooth functioning. Numerous sectors today, be the IT industry, the healthcare industry, government services, education, banking, etc. are reliant on Big Data because of its ability to

1. Drive major business decisions
2. Enable analytics
3. Find missing gaps and predict patterns for smoother functioning.

Because of the major role data plays, all of these businesses need structures to ensure that they can access it with ease. This is where the role of a Data Engineer becomes extremely important and Big Data training comes to use. It has been predicted that by 2024, there would be 149 zettabytes of data globally. The production of Big Data will also create opportunities for Data Engineers and according to LinkedIn’s 2020 Emerging Jobs Report, Data Engineering has a 33% annual growth. What gives any Data Engineer an extra edge over the others is a Big Data certification. Data engineering courses ensure that one is industry-ready with practical experience.


StackRoute’s Enterprise Big Data Engineering Program -

When one is entering a field as crucial as Big Data Engineering, it is important that they are equipped with transformative solutions. StackRoute has recognized the increasing demand and brings to you Enterprise Big Data Engineering, offering two specializations  under the same:


  • Enterprise Big Data Engineering & Machine Learning using Spark
  • Enterprise Big Data Engineering using Databricks & Delta Lake


Foundation Level

With the aim to enable early professionals to advance their career in Big Data Engineering, these two programs have a common foundation level that will run for 40 hours (6-8 weeks). By getting practical learning with Apache Spark and undergoing this Spark online training, learners will establish strong foundations in key software engineering principles and methodologies to build scalable data pipelines for analysis.



Specialization Level



    Big Data engineering and Machine Learning using Apache Spark

    The specialization level will run for 50 hours over the course of 10 weeks. Learners will use Apache Spark ML libraries in this Apache Spark Course to develop scalable real-world machine learning pipelines.



    Enterprise Big Data Engineering using Databricks &

    Delta Lake
    The specialization level will run for 30 hours over the course of 6-8 weeks. Learners will establish strong foundations in key big data pipelines using the latest technology of Azure Databricks (an Apache Spark based analytics platform optimized for the Microsoft Azure Cloud)


With these programs, one would be able to advance their career and upskill to meet the rising demand of Data Engineers, which, according to a Forbes survey, is one of the most sought-after job profiles across the globe today.

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Posted on 28 September, 2020
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