Introduction               

How to become a Data Engineer: With increasing reliance on data by industries such as IT, Insurance, Banking, Financial Services, Hospital, Healthcare, Internet, and many others, the demand for Data engineers has increased. A new category of software engineers, Data Engineer have thus gained importance due to the rise of Big Data and its key role in prime concerns of businesses. Data engineering is a relatively new profession which is basically a convergence of software engineering and data science.

This article will act as a step-by-step guide to help you know ‘How to become a Data Engineer?’ 

  1. What is a Data Engineer?
  2. What does a Data Engineer do?
  3. How do you become a Data Engineer?
  4. Data Engineer Responsibilities
  5. Data Engineer Skills

1) What is a Data Engineer?

Data Engineer is a kind of Software engineer who is in charge of data delivery, data storage and data processing. Data Engineer develops, tests, and maintains data storing infrastructure including databases, data processing systems, and data warehouse. 

In other words, he is in charge of the creation and maintenance of data workflow as well as data infrastructure underlying thereby.

2) What does a Data Engineer do?

Data Engineers convert raw data into information required by the data scientist for their analysis. There is a pool of data available which needs to be filtered as per the requirement of the company for analysis. This function of creating data pipelines for transforming and transporting data to relevant information. Data engineer thus need to use advanced programming skills such as data mining, data query, SQL, etc. using programming languages like Python, Scala, and such other languages.

3) How do you become a Data Engineer?

A Data Engineer is a Software engineer with skillsets for data analysis and statistics.

Step-by-step process on how to become a data engineer is as follow:

  1. Become a software engineer.
  2. Acquire the following skillsets:
  3. Programming languages including SQL, Python or R.
  4. Scripting languages for automation of repetitive time-consuming tasks.
  5. Working with Database containing structured as well as unstructured data. 
  6. Cloud computing for parallel processing of massive parallel processing (MPP) databases that run across several machines.
  7. Build a portfolio by choosing a discipline, formulating a problem statement, determining the dataset needed, and lastly gather the data and build a data pipeline for data storage and data query.

4) Data Engineer Responsibilities

Data Engineer is a vital job with the responsibility to expand and optimize data and data pipeline architecture and optimize the data flow and collect data for cross-functional teams.

The overview of the responsibilities of a Data Engineer are as follows:

  • Ensure that systems for storage and collection of data meet the industry standard and requirement of the business. 
  • Business data acquisition and integration of new data to the existing structure of the company.
  • Creation of customized software to the merger of systems and data analytics.
  • Installation and updating of Disaster Recovery protocols.

5) Data Engineer Skills 

  • Programming using Python and Scala
  • Automation, Shell Scripting and data processing in Shell
  • Database and Data processing
  • Scheduling workflow
  • Cloud computing
  • Internalize infrastructure using tools like Docker and Kubernetes.

Conclusion

Data Engineering is one of the constantly evolving field presenting various job opportunities. It is a profession that involves the use of new tools, lots of data, analyses and out of the box thinking to help meet the data needs of various data-driven industries.

If you are interested in making a career in the Data Science domain, our 11-month in-person Postgraduate Certificate Diploma in Data Science course can help you immensely in becoming a successful Data Science professional. 

ALSO READ

SHARE