Introduction
As we all know AWS (Amazon Web Services) is one of the most leading public cloud which provides 200+ services which includes storage services, networking over the internet and more.
It basically gives people and businesses a reliable and scalable infrastructure that they can use to run applications, store data, and set up different services without having to invest and manage physical hardware.
As per Forbes statistics, In 2024 companies will spend more than $1 trillion on cloud computing infrastructure for the first time.
So you may have the question “How to become an AWS Data Engineer?” To become an AWS Data Engineer, you’ll need to learn a wide range of skills that include both development (making software) and operations (which manages and maintains systems).
In this blog, I will explain a step-by-step guide to becoming an AWS data engineer. What is an AWS Data Engineer? What skills are required to become an AWS data engineer?
Let’s first understand What is an AWS Data Engineer?
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What is AWS Data Engineer?
The main and most important responsibility of AWS data engineers is to manage various AWS services. It involves using AWS services to manage and analyze data, helping companies extract valuable insights and improve decision-making.
In Simple terms we can say that Data engineers should know how to work with databases and software engineers should know how to code.
Similar to that, AWS data engineers do the same work as regular data engineers do, but the main difference is that they only work on AWS Services. If you are interested in working with data and have some knowledge of AWS cloud computing, then AWS Data Engineering is the best career option for you.
Also Read: What is VPC peering in AWS?
How to become an AWS Data Engineer?
Let’s explain “How to become an AWS Data Engineer” step-by-step guide:
Step 1: Understand the Basics of Data Engineering:
- First you have to learn the basic ideas of data engineering, such as how to store, clean, process, and transform data.
- You have the basic understanding of databases, programming languages, and cloud platforms such as AWS.
- Learning these basics will help you build data systems that work well so that businesses can make better decisions.
Step 2: Build a Strong Foundation in Cloud Computing:
Understand the basics of cloud computing like what is cloud computing such as IaaS, PaaS and SaaS services.
Step 3: Learn AWS Fundamentals:
- Learn basic AWS services, such as S3 (Simple Storage Service), EC2 (Elastic Compute Cloud), AWS Lambda, and more.
- Get hands-on experience with the AWS Management Console. This practical experience will not only help you get better at using AWS services, it will additionally prepare you properly for real-world data engineering tasks in a cloud environment.
Step 4: Explore Big Data on AWS
- Learn about AWS Big Data services, including EMR (Elastic MapReduce) and Redshift.
- Learn how AWS handles processing and analyzing big amounts of data.
Step 5: Learn Database Management:
- Explore AWS database services like RDS (Relational Database Service) and DynamoDB.
Step 6: Develop Programming Skills:
- Learn programming languages commonly used in data engineering, such as Python and SQL.
- Understand how to use these languages for data manipulation and transformation.
Step 7: Explore Data Processing Tools:
- Learn AWS data processing tools which are very important , including AWS Glue and Athena.
- Understand the concepts of ETL (Extract, Transform, Load) processes.
Step 8: Gain Practical Experience through Projects:
After gaining all these knowledge you have to apply your knowledge in real-world scenarios by working on hands-on projects.
Step 9: Pursue AWS Certifications:
- Start preparing yourself for AWS Certified Big Data – Specialty or AWS Certified Database – Specialty.
- Keep one thing in mind: Certifications validate your expertise and enhance your credibility.
Also Read: AWS Lambda Interview Questions
What Skills do you need for AWS Data Engineering?
Before start learning AWS Data Engineer you must have these prerequisites skills –
- You must have knowledge of Python Programming
- In databases you have a solid understanding of SQL is important. Familiarity with NoSQL databases like Cassandra and DynamoDB is also more advantageous
- Familiarity with the basic Linux command is very helpful for navigating and managing AWS services
- Understanding of cloud computing concepts like IaaS, PaaS, SaaS and benefits is helpful
- Basic knowledge of networking concepts is also important
- Having knowledge of big data concepts and tools like Hadoop and Spark is important for learning in the data field.
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What are the Core technologies involved in AWS Data Engineering?
Core Technologies:
| Technology | Explanation |
| Programming Languages | Python is the primary language in the data field, Java and Scala are also common. |
| Databases | Understanding relational databases – SQL & NoSQL databases like DynamoDB. |
| Linux Commands | Basic understanding of linux commands for data engineers like cd,ls, cp, mv, rm, chmod and more. |
AWS Services:
| AWS Service | Explanation |
| AWS S3 | Object storage service for storing and retrieving large amounts of data |
| AWS EC2 | Provides virtual servers in cloud computing platform |
| AWS VPC | Virtual Private Cloud for creating isolated network environments in the AWS cloud |
| AWS IAM | Identity and Access Management for secure control of AWS resources. |
| AWS Redshift | Fully managed data warehouse service which is mainly used for large-scale data analytics. |
| AWS Kinesis | Services for real-time processing of streaming data |
| AWS Athena | Query service for analyzing data stored in S3 using SQL database |
| AWS Glue | AWS Glue is mainly used for data integration, fully managed extract, transform, and load (ETL) service |
| AWS EMR | Elastic MapReduce for processing large amounts of data using big data tools like Hadoop and Spark. |
Is AWS Data Engineer A Good Career Option In 2024?
Yes, AWS Data Engineer is a good career option in 2024 and beyond.
Here are some Reasons –
High Demand In Today’s IT Market:
- There is a big need for skilled AWS Data Engineers, and that need is only going to keep growing over the next few years. This is because organizations are putting more value on data and using cloud computing tools like AWS.
- The AWS Data Engineer job is one of the top new jobs on LinkedIn’s 2023 Emerging Jobs Report. It is expected to grow by 26%.
Lucrative Salary:
As per Ambition Box Report Starting salaries for AWS Data Engineers are –
- For Freshers – ₹3.7 Lakhs to ₹4.5 Lakhs per year.
- With additional experience and expertise – ₹10 Lakhs to ₹15 Lakhs per year
- With specialized skills – ₹20 Lakhs annually
Note: Salaries depend on experience, location, and most important skills.
Career Growth Opportunities:
AWS Data Engineers have a lot of chances to move up in their careers. As they get better, they can become AWS Data Architects or AWS Data Scientists, AWS Data Engineers.
The Demand Of Cloud Computing:
The amount of data in the world is growing exponentially. As per Forbes statistics, In 2024 companies will spend more than $1 trillion on cloud computing infrastructure for the first time.
The Growth of big data:
There is a huge increase in the amount of data in the world, which is making businesses need people to help them store, handle, and analyze this data.
As per MarketsandMarkets statistics the Big Data Market will grow at a compound annual growth rate (CAGR) of 11.0% and reach $273.4 billion by 2026.
Conclusion
In this blog we conclude that –
- Becoming an AWS Data Engineer opens many job opportunities
- AWS Data Engineers can work in a wide range of fields, from banking and healthcare to e-commerce and technology. This makes the job market very flexible.
- You must be creative and find solutions to problems.
- Knowledge and experience make it easier to choose the proper path for your future.
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