AWS Data Engineer Salary

What is the Salary of AWS Certified Data Engineer Associate?

Data engineering, particularly with Amazon Web Services (AWS), has evolved as an appealing and financially rewarding career path.

The growing need for data engineers has elevated the salary spectrum within the field. But first, there’s an important question to answer before diving into this field: “What does an AWS Data Engineer salary look like?”

No need to fret! Keep reading this blog.

This article encompasses all the essential information about the AWS Certified Data Engineer Associate, delving into the salary of the AWS Certified Data Engineer Associate and thoroughly examining the factors that influence the salary range.

To shine in data engineering, taking the AWS Certified Data Engineer Associate certification can be an ideal choice.

Let’s get started!

Role of Data Engineers in Today’s World

Data engineers play a crucial role in developing the systems that handle data storage, extraction, and processing. They are responsible for constructing and maintaining databases for applications while overseeing the infrastructure necessary for their operation. 

As a data engineer, your responsibilities may include managing a SQL data store and a MongoDB NoSQL data warehouse, ensuring accessibility and functionality.

Collaborating within a team alongside software engineers, developers, data analysts, and designers, data engineers contribute their expertise to gather and manipulate data, driving essential business objectives. 

The specific duties of a data engineer can vary across organizations, including tasks such as: 

  • Designing efficient data store indexes
  • Selecting appropriate storage technologies (SQL or NoSQL)
  • Maintaining data stores
  • Replicating data across multiple machines
  • Tuning data warehouses
  • Creating and validating query plans
  • Identifying patterns in historical data
  • Analyzing and optimizing database performance

AWS Certified Data Engineer-Associate Certification: An Overview

AWS has recently introduced the AWS Certified Cloud Data Engineer-Associate Certification Exam. 

AWS Certified Data Engineer-Associate Certification Exam serves as an excellent entry point for individuals seeking to delve into advanced specialty themes in AWS, even without prior data experience.

Conversely, for those already engaged in data-related roles, this certification offers a valuable opportunity to deepen their comprehension of AWS by utilizing specialized services they likely already engage with.

While acquiring these skills was always possible without formal certification, the introduction of a structured certification pathway not only encourages learners to pursue certification but also motivates training providers to address skill gaps by offering specialized guidance and resources.

This certification confirms your expertise in core AWS data services, assessing your skills in configuring data pipelines, proficiently managing monitoring and troubleshooting, and optimizing performance while adhering to industry best practices.

However, obtaining AWS Data Engineer certification can significantly enhance earning potential by validating proficiency in core AWS data services, data pipeline configuration, and effective management of monitoring and troubleshooting. 

Role of an AWS Certified Data Engineer Associate

For those new to the field of data engineering, enrolling in the AWS Data Engineer Certification Beta course is a valuable option. 

The AWS Certified Data Engineer Associate Certification Exam (DEA-C01) follows the Associate-level tests for Solutions Architects, Developers, and SysOps Administrators, making it the company’s fourth Associate-level certification.

AWS Certified Data Engineer Associates were solely responsible for the following tasks:

  • Ingesting and transforming data 
  • Orchestrating data pipelines when deploying programming concepts 
  • Operationalizing, maintaining, and monitoring data pipelines
  • Identifying the most suitable data storage solution, crafting effective data models, and organizing data schemas efficiently
  • Overseeing the entire lifecycle of data, from creation to disposal
  • Evaluating and ensuring the quality of data through thorough analysis
  • Enforcing proper measures such as authentication, authorization, data encryption, privacy, and governance for effective data management

AWS Data Engineer Salary 

AWS Data Engineer Salaries in India

The average annual salary for an AWS Data Engineer in India is ₹21,20,567. Additionally, there is an average additional cash compensation of ₹13,87,883. The range for this additional cash compensation can range from ₹13,87,883 to ₹13,87,883.

AWS Data Engineer Salaries in the USA

The average annual salary for an AWS Data Engineer in the United States is found to be $129,716. In hourly terms, this averages approximately $62.36 per hour. Every week, it is equivalent to $2,494, and monthly, it amounts to $10,809.

Factors Influencing AWS Data Engineer Associate Salary 

The salary of an AWS Certified Data Engineer Associate is influenced by a variety of factors that collectively shape the compensation landscape for professionals in this field. 

Understanding these factors is crucial for both aspiring data engineers and those looking to negotiate their salaries. 

Here are key elements that influence the salary of an AWS Certified Data Engineer Associate:


Experience Level

Salaries often differ based on experience level. It means entry-level candidates will get a lower salary compared to those who have several years of hands-on experience in the data engineering field.

For example

Entry-level AWS Certified Data Engineer Associate can get an average pay of $124,786 per year while most of the AWS Senior Data Engineer salary will be around $175,000 per year.


Even though education is significant, taking relevant certification courses can help move on to data engineering jobs. The AWS Data Engineer Associate can be maximized if you hold certifications such as AWS Certified Big Data – Specialty certification, Google Professional Data Engineer, etc.


Location stands out as one of the paramount factors influencing the AWS Data Engineer Salary. The geographical setting where a professional works significantly shapes the compensation landscape, reflecting variations in living costs, market demands, and economic conditions. 

The cities where data engineers can earn the highest salaries include Seattle, Maryland, and Washington, with average salaries of over $2,11,350 /year. 

Skill Set

To shine in the data engineering field, you must possess the following skills:

  • ETL Tools: Understanding and utilizing various ETL tools are crucial for effective data management. These tools enable professionals to extract data from diverse sources, transform it according to specific requirements, and load it into databases or data warehouses. Examples of popular ETL tools include Apache NiFi, Talend, Informatica, and Microsoft SSIS.
  • SQL: SQL (Structured Query Language) is a fundamental language for interacting with databases. Given that substantial volumes of data are typically stored in expansive data warehouses, proficiency in SQL is imperative. It empowers data engineers to retrieve, manipulate, and manage data efficiently.
  • Python: Programming languages play a pivotal role in performing ETL tasks and data management activities. Python stands out as one of the most versatile and widely used languages for these purposes. Data engineers often leverage Python for scripting, automation, and executing various data-related tasks.
  • Big Data Tools and Cloud Storage: Dealing with extensive datasets is a common aspect of a data engineer’s role. Therefore, familiarity with big data tools such as Hadoop, Spark, and cloud storage solutions like Amazon S3, Google Cloud Storage, and Azure Data Lake Storage (ADLS) is crucial. These tools streamline the handling and processing of large-scale data.
  • Query Engines: Proficiency in query engines like Apache Spark and Apache Flink is essential for running queries against sizable datasets. These engines enable data engineers to process and analyze data efficiently, making them indispensable tools in the data engineering toolkit.
  • Data Warehousing Concepts: Data engineers are responsible for maintaining data warehouses, making it vital to have a comprehensive understanding of data warehousing concepts. This includes knowledge of key components such as Enterprise Data Warehouse (EDW), Operational Data Store (ODS), and Data Mart. Mastery of these concepts ensures effective data storage, organization, and retrieval.

Possessing proficiency in tools such as Python and SQL can secure an average salary of 8.5 and 8.6 LPA, respectively, for a data engineer. 

Following closely are skills related to Hadoop and ETL, garnering an average salary of 9 LPA. To maximize earnings, expertise in Amazon Web Services (AWS) and Apache Spark is pivotal, as they can lead to an average salary of 9.8 and 10 LPA, respectively.


Data Engineers are paid more when working in larger firms such as Google, Apple, Meta, etc.

As per the study, In India, the data engineers who work at Cognizant can make up an average pay of about ₹819,207/ year. In IBM, they offer good pay to AWS data engineers which is about ₹950,000/ year.

Job title variations

Data engineer job titles differ based on the company, tasks, and skills they have. Here are some job titles that data engineers can hold:

  • Enterprise Data Architect: $172,872
  • AI Engineer: $126,774
  • Cloud Data Engineer: $116,497
  • Hadoop Engineer: $143,322
  • Database Architect: $143,601
  • Data Science Engineer: $127,966
  • Big Data Engineer: $116,675
  • Information Systems Engineer: $92,340

How to improve AWS Certified Data Engineer Associate Salary?

To enhance your AWS Certified Data Engineer Associate salary, consider the following strategies:

  • Continuous Learning: Stay updated on the latest AWS technologies and best practices. Attend training sessions, webinars, and workshops to expand your knowledge.
  • Earn Additional Certifications: Obtain other relevant certifications to demonstrate a diverse skill set. This can make you more valuable to employers and potentially lead to a higher salary.
  • Gain Practical Experience: Apply your knowledge through hands-on projects and real-world scenarios. Practical experience is highly valued and can set you apart in the job market.
  • Build a Strong Professional Network: Connect with other professionals in the field, attend industry events, and participate in online forums. Networking can open up new opportunities and provide insights into salary trends.
  • Showcase Your Achievements: Highlight your accomplishments on your resume and LinkedIn profile. Quantify your impact on projects and emphasize how your skills have positively contributed to business objectives.
  • Negotiation Skills: Develop effective negotiation skills when discussing salary with potential employers. Research industry salary benchmarks and be prepared to make a compelling case for your value.
  • Specialize in High-Demand Areas: Focus on specialized areas within AWS that are in high demand. This could include specific data analytics tools, machine learning, or database management skills.
  • Seek Leadership Roles: Transitioning into leadership positions can often lead to higher salaries. Develop your leadership skills and take on responsibilities that demonstrate your ability to lead and manage teams.
  • Stay Informed About Market Trends: Keep track of industry trends and market demands. If you can align your skills with emerging technologies and trends, you may find yourself in higher demand.

Key AWS Services to Prioritize for the DEA-C01 Exam

To effectively prepare for the AWS Data Engineer Associate exam, it is essential to focus on specific concepts and AWS services to optimize study time and avoid unnecessary topics.

It is highly recommended to dedicate more time to comprehending the following AWS services:

  • Amazon Athena
  • Amazon Redshift
  • Amazon QuickSight
  • Amazon EMR (Amazon Elastic MapReduce)
  • AWS LakeFormation
  • AWS EventBridge
  • AWS Glue 
  • Amazon Kinesis 
  • Amazon Managed Service for Apache Flink
  • Amazon Managed Streaming for Apache Kafka (Amazon MSK)
  • Amazon OpenSearch Service


Is it worth getting a certificate in the data engineering field?

Yes, obtaining a data engineering certificate is worthwhile for several reasons. It serves as a proven and effective way to enhance your earning potential. Additionally, it demonstrates to potential employers that you are committed to staying updated on the latest advancements in the field and showcases your dedication to continuous learning. 

Does an AWS Data Engineer require coding knowledge?

No, it is not necessary to know coding if you want to become an AWS Data Engineer.

What skills are required for an AWS data engineer?

To become an AWS Data Engineer, you need the following skills to execute Data Engineering tasks effectively:

  • SQL Skills
  • Data Modelling
  • Hadoop for big data
  • Python
  • AWS Cloud services

What is AWS Data Engineering?

AWS Data Engineering entails the gathering of data from various sources to be stored, processed, analyzed, and visualized, and the creation of pipelines on the AWS platform.


Hope this blog details the AWS Certified Data Engineer Salary and what are the factors that impact the AWS Data Engineer Salary. 

As the demand for skilled data engineers continues to rise, obtaining the AWS Certified Data Engineer Associate credential not only validates your expertise but also enhances your earning potential. 

To further delve deeper into the data engineering world, try our hands-on labs and sandbox.

About Basant Singh

Basant Singh is a Cloud Product Manager with over 18+ years of experience in the field. He holds a Bachelor's degree in Instrumentation Engineering, and has dedicated his career to mastering the intricacies of cloud computing technologies. With expertise in Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), he stays current with the latest developments in the industry. In addition, he has developed a strong interest and proficiency in Google Go Programming (Golang), Docker, and NoSQL databases. With a history of successfully leading teams and building efficient operations and infrastructure, he is well-equipped to help organizations scale and thrive in the ever-evolving world of cloud technology.

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