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Table of contents
1.
Introduction
2.
About IBM 
3.
Roles and Responsibilities
4.
Skills and Experience Required
4.1.
Required Technical and Professional Skills 
4.2.
Preferred Technical and Professional Skills
5.
Salary
6.
Benefits and Perks
7.
Roadmap to becoming a Data Engineer
8.
Career map of a Data Engineer
9.
Preparation Strategy and Resources
10.
Frequently Asked Questions
10.1.
What is the role of a Data Engineer at IBM?
10.2.
With whom does a Data Engineer need to work and collaborate?
10.3.
How long does it take to get an offer from IBM?
10.4.
How many rounds are there for experienced candidates in IBM interviews?
10.5.
What is the hardest part about being a Data Engineer?
11.
Conclusion
Last Updated: Mar 27, 2024

Data Engineer at IBM

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Introduction

Hello Ninjas!

With the growing realization of the power of data, the demand for skilled professionals who can use raw data to transform, analyze and evaluate has increased. One such job is the Data Engineer. A data engineer helps transform the raw data into usable form and designs systems to collect, manage and transform the data. Everyone that wants to be a data engineer aspires to be a part of top Tech companies, IBM being one of them.

Data Engineer at IBM

Let’s see what the role of a Data Engineer at IBM is like and discuss the strategies to be one. But before that, let’s have a brief introduction to IBM.

About IBM 

IBM stands for International Business Machines. It is an American multinational technology company. Charles Ranlett Flint founded the company in 1911. IBM is known for developing and selling software, middleware, and hardware. 

IBM Logo

The company has headquarters in Armonk, New York. The company is best known for cloud computing and data analytics. The company has more than 2,82,100+ employees. Top inventions by IBM include ATMs, magnetic strip cards, hard disks, etc.  

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Roles and Responsibilities

As we all know, today’s era is called the ‘Information Era’, where we produce zettabytes and exabytes of data. There is a data flood but a lack of information. Using this raw data and applying data mining techniques, we can find interesting relations and patterns but the data that is collected from various sources is not clean and refined and is not used as it is by Data analysts or ML engineers. In order to remove noisy, inconsistent data and transform it into a usable form, Data Engineers are required.

Roles and Responsibillities

Data Engineers seek to make data accessible in a usable form so businesses and institutions may review, analyze, and enhance their performance. This work mostly entails developing new systems that collect, handle and turn raw data into useful forms. The Data Scientists and Business Analysts then utilize this form to interpret and do their specialized jobs.

The points below summarize the responsibilities of a Data Engineer at IBM.

  • Create, evaluate, and support future-ready data solutions for clients in various industry verticals.
     
  • Create, evaluate, and support batch and near real-time data flows and pipelines.
     
  • Display knowledge of data architectures, contemporary data platforms, big data, machine learning and artificial intelligence, analytics, cloud computing, data governance, and related technologies.
     
  • To ensure that risks are understood and communicated.

Skills and Experience Required

Skills

In this section, we will look at both, the required and preferred skills and experience for the role of Data Engineer at IBM.

Required Technical and Professional Skills 

  • The candidate requires at least two years of relevant experience.
  • Knowledge of designing business systems and models
  • Excellent practical knowledge of DataStage, Alteryx, Informatica, and SSIS
  • Possess extensive experience writing complex Python and Spark for Data Processing codes.
  • Well-versed in OLAP techniques and data warehouse schemas.

Preferred Technical and Professional Skills

  • The capacity to manage and make decisions regarding resources and priorities that are in conflict.
  • The capacity to delegate as necessary.
  • Must be a capable team leader.
  • The capacity to oversee data transformation projects, including numerous rookie data engineers
  • Strong communication abilities—oral, written, and interpersonal—for interaction at all organizational levels.
  • The ability to express technological answers and complex commercial problems clearly.

Salary

Freshers and employees below two years of experience can make an annual income of 7-8 lakh rupees. Employees with experience between four and ten years may expect an average pay of 10-11 lakh rupees per year as an IBM Data Engineer in India. The average take-home salary ranges between 77-79 thousand rupees per month.

Salary

The tabular representation of the salary of a Data Engineer at IBM is given below.

(The figures presented above are subject to change by IBM)

Benefits and Perks

IBM is a well-known company with a positive workplace culture and good working conditions. The benefits an employee gets entirely depend on the project they are working on or the business unit to which they will be assigned. But apart from those benefits and perks, there are some constant benefits of being at IBM which is -

🩺Health Insurance

 🛣️Leave

 🏢Flexibility at work

🍔Meals

🏖️Team outings

👨‍🏫Soft skill training

📚Job training

💰Reimbursement

💸Financial perks

🎗️Health and wellness

👪Childcare

🧓Retirement plans

🧑🏼‍🤝‍🧑🏽Opportunities to network and connect

Roadmap to becoming a Data Engineer

We present to you a well-defined Roadmap to becoming a successful Data Engineer.

Roadmap

 

  1. Become a proficient programmer: Data engineering requires a good grip on Software engineering skills and data science knowledge. To get started in this field, a person should learn and achieve proficiency in languages like Python and Scala, the most in-demand languages in this industry. You can find resources to learn to program in the links attached to this blog's resources section.
     
  2. Learn about Scripting and automation: As a Data Engineer, you should know how to automate manual and tedious tasks. This helps you deal with large datasets more efficiently.
     
  3. Clear knowledge about Databases: The importance of learning about Databases and their management cannot be emphasized enough for this role. Learn SQL, Mongo, and other famous databases and about how to operate it. You can find the resources to start learning in this blog.
     
  4. Learn about Data processing Techniques: Data that you will deal with in this profession is often unclear, noisy, and unorganized, so before you use it in your projects, you should be well-versed in data cleaning and processing techniques.
     
  5. Scheduling your workflow: Mastering any profession requires planning and scheduling your workflow. You can use many online tools to manage and schedule your workflow to avoid confusion and clarity.
     
  6. Study about Cloud and Cloud computing: Engineers who can work on cloud computing tools are in high demand as companies increasingly prefer to invest in cloud computing for data storage rather than bulky hardware systems. The three most popular cloud service platforms are Google Cloud Platform, Amazon Web Services, and Microsoft Azure. All three platforms offer official certifications, which can be obtained through official websites.
     
  7. Be in touch with the current trends: If you've come this far, don't be disheartened if you don't feel you completely understand the data engineering landscape. It's a vast field that is constantly evolving. What matters most is that you use the right tool for the job and don't overcomplicate the big data solutions you create. All you need is to keep an eye on the current industry trends and keep learning.
     
  8. Learn Data Engineering by applying your skills to practical projects: Keep taking up projects that help you refine your skills and understand the technologies required to be a successful data engineer.

Career map of a Data Engineer

Career Map

In this section, we will discuss the career prospects of a Data Engineering career. So, as your experience grows as a Data engineer in any software firm, you are provided with better opportunities. Data Engineering is not an entry-level role. Mostly software engineers or business intelligence analysts take up the role of Data Engineer and as you advance in your career, you may be provided with the managerial role or data architect, solution architect, or machine learning engineer.

Preparation Strategy and Resources

As we saw above, the Data Engineer position at IBM has numerous benefits, but it requires a lot of hard work. Along with hard work, smart work is needed as well. The smart work would be to follow effectively designed courses and study plans with complete discipline!

 

Preparation and resources

Check out the following articles by clicking on the link to access resources that will boost your preparation:

PythonRefer if you are looking for help learning Python, one of the most in-demand programming languages for Data engineers.

Data Warehousing and Data MiningAs mentioned above, knowledge about Data mining and Data Warehousing are some crucial skills that Cisco expects to see in the candidates for the Data Engineer position.

Database Management Systems: To be able to work efficiently with databases, refer to this article to start from scratch and reach an advanced level. DBMS knowledge is one of the most crucial skills a Data Engineer should possess.

AptitudeThis is an essential skill required to clear any interview.

Big DataRefer to this article to learn more about Big Data.

Guide to Kaggle: This is a complete guide to Kaggle for Data Science.

Being skilled at problem-solving has become a necessary skill for any tech-related job. We bring you a well-curated list of problems and resources to practice from to master problem-solving abilities:

Test-series: Follow the test series to get a good grip on concepts and test your abilities.

Problems: Master Data Structures and Algorithms by solving the issues.

Interview bundle: This link contains the various questions asked during the interview in multiple companies.

Contests: Follow this link if you want to practice in a coding contest hosted by the coding ninjas for more practice.

Guided paths for coding interviews: This link contains the complete guide on what to do before an interview.

Check out the courses mentioned below to learn more about Machine learning, Data Science, and Data Analytics.

Machine Learning

Data Analytics

Data Science

 

Also, check out the following video that guides you on how to be placement ready in 100 days.

Frequently Asked Questions

What is the role of a Data Engineer at IBM?

Data engineers are in charge of converting raw data into information that can be used for analytics and corporate decision-making. A data engineer can develop massive data processing systems for the organization and know how to use technologies to address big data issues. Data engineers create, maintain, test, and assess big data solutions within enterprises.

With whom does a Data Engineer need to work and collaborate?

Data scientists and Data engineers collaborate to increase information quality and accuracy, allowing enterprises to make more responsible decisions. They work with leaders from across the organization to support business choices.

How long does it take to get an offer from IBM?

After applying, you need to wait for at least 2-3week till the process of recruitment starts. Once you clear all your rounds, you will receive a job offer letter from IBM after 10-20days from your final interview.

How many rounds are there for experienced candidates in IBM interviews?

For experienced individuals, the IBM interview process typically consists of two or three rounds. The Technical, Resume Shortlist, and HR phases of the IBM interview process are the most frequent for experienced candidates.

What is the hardest part about being a Data Engineer?

So the most challenging aspect of the work is grasping the different technologies to master while also comprehending the in-house data teams' short-term and long-term demands to identify which methods are applicable.

Conclusion

In this blog, we discussed the role of a Data Engineer at IBM. We looked had a brief introduction about IBM, the salary and perks that it provides to its Data Engineers, and the job expectations it has in return. We also discussed the essential skills required to grab the position of a Data Engineer in a reputed company like IBM. The blog has resources linked to it to help the candidates prepare well for their interviews and other rounds of becoming a Data Engineer.

Check out IBM Interview Experience to learn about their hiring process.

To know more about the IBM Jobs, the way to get into IBM, or different profiles, you can check out these articles:

To learn more about DSA, competitive coding, and many more knowledgeable and interesting topics, please look into the guided paths on Coding Ninjas Studio. You can also enroll in our courses and check out the mock test and problems available. Do check out our interview experiences and interview bundle for placement preparations.

Keep learning and keep growing!

Happy Reading!

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