Amazon Web Services (AWS) is a leader in the cloud services as well as data engineering space. It has a collection of some impressively robust services and tools for handling data at scale. It is the preferred cloud service provider (CSP) for leading internet businesses like Netflix, Facebook, LinkedIn, etc. This is a complete guide on how to become an AWS data engineer since this profile is high in demand. Let's begin with who is an AWS data engineer.
Who is an AWS Data Engineer?
An AWS data engineer is one who has the same duties as any regular data engineer. The only difference is that these duties are exclusive to the Amazon Web Services cloud platform. They create, upgrade and maintain this platform's infrastructure for running applications. The next segment covers an answer to 'what does an AWS data engineer do'.
What Does an AWS Data Engineer Do?
Amazon Web Services engineers carry out many different tasks. They preserve data integrity and build data models for collecting information from different sources. They look for patterns in the data that may be further used for guiding business decisions and even designing strategies. They continually look for new data sources and technologies to be incorporated into both existing and future projects.
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AWS Data Engineer Roles and Responsibilities
There are many different AWS data engineer roles and responsibilities. Complete knowledge can only be learned by enrolling in a good course and through practical experience.
- Construct data models for gathering information from different sources and storing it.
- Boost performance by improving database design.
- Maintain data integrity by developing backup and recovery mechanisms.
- Research new data sources and technologies for current projects.
- Create new apps to use existing datasets.
- Find insights or patterns in data for better business choices and strategy building.
- Upgrade old code and add new features to current apps to keep them updated.
- Use Amazon Simple Storage Service to retrieve data.
- Improve the infrastructure for more storage capacity and better performance.
- Design and implement security measures to protect data from illegal access or abuse.
- Use AWS tools for data integration.
- Build data pipelines and handle gigantic datasets.
- Implement firewall security of AWS through AWS security groups.
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Guide On How To Become A Certified AWS Data Engineer
This guide includes the three biggest steps for becoming an AWS Data Engineer. The first step is to gain all important skills and that can be done with the right resources. The second step thus is to pick a reliable learning source. Finally, it is about getting certified with the best certificate.
1. Master Important Skills
Data engineers must know everything about Amazon Web Services to execute their tasks. Many technical and soft skills are involved in this process.
- Soft Skills - These skills are not specifically related to the job but are needed to excel in any workplace. Some common ones to have are analytical thinking, problem solving skills, good communication, teamwork and attention to detail.
- Technical Skills - Here are the most important technical skills a data engineer for AWS must have.
- Programming/ Scripting Languages - SQL, Python and Java (optional).
- Other Competencies - Data governance, data compliance and data privacy.
Learning is not always restricted to a classroom. There are different learning methods that can be chosen for learning.
- Online Courses & Tutorials - Many platforms offer online courses to learn this technology. These courses also lead to certification as the right knowledge is learned under industry professionals.
- Self-paced Learning - Such learning includes picking online resources like recorded sessions to learn at one's own pace. This does not interactive sessions but recorded videos of those sessions.
- Bootcamps or Workshops - Both these are great for intensive and hands-on learning. These are a big plus when looking for a job.
- Communities - The right way to engage with like-minded people is by becoming part of different virtual and offline communities. Talk about and discuss with people of similar interests to learn more about the topic.
3. Get Certified
AWS offers many different relevant certificates according to the individual's needs. Some of them are -
- AWS Certified Cloud Practitioner - This is the first step in earning more AWS certifications. It reflects one's basic understanding of AWS Cloud along with its terms and services. Beginners to the cloud or IT benefit the most.
- AWS Certified Solutions Architect (Associate) - This credential focuses on designing performance and cost and optimized solutions. Professionals who have working knowledge in other cloud services with understanding and experience of mapping on-premises to the cloud benefit from this one.
- AWS Certified Developer (Associate) - This credential reflects one's expertise in important AWS best practices and services. These holders can build, troubleshoot and deploy cloud based apps on AWS. Experienced individuals in AWS technology having in-depth knowledge of any top programming language benefit. The aspirant should have experience of working in any cloud service with understanding and experience of mapping on-premises to the cloud.
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- AWS Certified Database (Specialty) - This credential is to show expertise in maintaining, recommending and designing optimal AWS DB solutions. The aspirant should have an understanding of the different features of AWS DB services.
- AWS Certified Data Analytics (Specialty) - This credential is a testament in using AWS data analytics services as well as data lakes for gaining insights from data. Individuals must have knowledge of AWS data analytics services and their working together. Understanding of AWS data analytics services' working is also needed.
These engineers have a very high level of knowledge because they know many tools, technologies and platforms. These five are the must know tools for AWS data engineers today.
- AWS Glue - It is a serverless data integration solution for discovery, transportation, integration and preparation of data from different sources. This data goes through these processes for data analytics, application development and machine learning. It consolidates business intelligence technology and data warehouses.
- AWS Athena - This is a query service for quickly examining data in Amazon S3 by using conventional SQL. It is serverless and has no infrastructure to manage. The user only pays for the executed queries and is also simple to use.
- AWS Redshift - This tool uses SQL queries for analyzing semi-structured and structured data across operational databases, data lakes and data warehouses. It uses AWS designed hardware and ML for cost effective performance at any intended scale. It has built-in optimizations for effectively searching this data and automatically detects Star Schema data structures and.
- AWS Kinesis - This tool collects, processes and analyzes real-time streaming data for quick access to additional information and timely insights. It ingests real time data for data analysis and Machine Learning.
- AWS Identity and Access Management (IAM) - It specifies what/ who can access AWS resources and services. It analyzes access for adjusting permissions across AWS by centrally managing fine-grained permissions.
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Conclusion For How To Become an AWS Data Engineer
Become an AWS data engineer by learning to write code for a good career in this niche. Tackle some challenging and changing problems in the field of data engineering today. Now is the best time to become an AWS data engineer as there's always more to uncover.
FAQs on AWS Data Engineer
Q1. What skills are required to become an AWS data engineer?
They should be proficient in its services like S3, Redshift, Glue and EMR. Strong knowledge of ETL processes, SQL, Python, Apache Spark and Hadoop is also a must for them.
Q2. Which certifications are beneficial for an AWS data engineer?
The certificates are valuable to prove the proficiency of an individual in AWS. There are various credentials available for them including AWS Certified Data Analytics - Specialty and AWS Certified Solutions Architect - Associate.
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