Data Architect Vs. Data Engineer (With Duties And Salaries)

By Indeed Editorial Team

Published 10 May 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

In most businesses, data is a vital resource for identifying trends and making smart business decisions. The process involves gathering, organising, cleaning, maintaining, securing and converting data into information that professionals use to make predictions and forecasts. Knowing how data architects and data engineers assist in various stages of data management can help you decide whether to pursue a career in either of these fields. In this article, we discuss the differences between a data architect vs. data engineer, outline their roles and responsibilities, explore their career paths and find out their average salaries.

Related: How To Become A Software Architect (Duties And Salary)

Data architect vs. data engineer

You can learn more about the differences between a data architect vs. data engineer and determine if you want to pursue a job in this field by understanding their respective roles and responsibilities. A data architect devises the architecture and blueprint for a company's data. These professionals typically have extensive experience with data modelling, data integration and data design. Contrary to this, data engineers implement designs based on the guidelines created by data architects. They have a solid foundation in programming and software engineering.

What does a data architect do?

As an IT specialist, a data architect designs and manages data systems, develops data management strategies, coordinates the use of multiple data sources within an organisation and enables the integration of new data technologies into existing IT systems. These professionals also have the following responsibilities:

  • developing and implementing effective database solutions for storing and retrieving company data

  • evaluating client operations, applications and programming to determine the database structural requirements

  • making sure database implementation procedures are compliant with all applicable regulations

  • organising and installing information systems to ensure smooth operations

  • providing management and executive teams with informative reports on database design and architecture

  • ensuring the smooth migration of data from legacy systems to updated systems

  • conducting regular tests, troubleshooting and integrating the latest features to monitor system performance

  • providing recommendations for improving new and existing databases

  • providing training and individual assistance to staff

  • providing support by promptly responding to system problems

Related: Top 20 Big Data Tools: Big Data And Types Of Big Data Jobs

What is a data engineer?

A data engineer is an expert in information technology and computer science who creates algorithms based on raw data sets to generate insights. Their work involves the design, construction, testing and maintenance of data-storing architecture, such as databases and large-scale data processing systems. Some of their other responsibilities include:

  • ensuring architecture aligns with business needs

  • communicating with the client and coworkers to ensure that they clearly understand the requirements

  • building data systems and pipelines to facilitate end-to-end products

  • modifying existing frameworks to make them more efficiency

  • ensuring the backup of data and its easy retrieval in case of system failure

  • making raw data suitable for data scientists to work with

  • ensuring data quality and efficiency

  • keeping track of industry standards and technological advances that can improve the framework structure and design

Related: What Does A Data Scientist Do? And How To Become One

Skills essential to becoming a data architect

If you are looking to pursue a career as a data architect, it is essential to have some of the following skills:

  • Databases and operating systems knowledge: Having extensive experience with both SQL and NoSQL databases, these experts are able to assess their benefits and disadvantages in terms of how to set them up across diverse operating systems and environments.

  • Data architecture: These professionals are familiar with the best practices associated with enterprise data warehouse development, along with a thorough understanding of the data infrastructure of an organisation and the way systems interact.

  • Data modelling, design, integration and management: Understanding data modelling, design and implementation is the key to becoming a data architect that helps them design the blueprint for organisational data.

  • Data security and governance: These types of employees understand how to implement processes, roles, policies, standards and metrics to ensure the efficient and effective use of data.

  • Leadership: Data architects are visionaries who are responsible for creating a framework that is not only reliable but also highly scalable and secure. They assist professionals who translate the framework into an implementation plan.

Skills essential to becoming a data engineer

If you are looking to pursue a career as a data engineer, it is essential to have some of the following skills:

  • Data wrangling: This refers to gathering, filtering, enhancing and transforming data into the desired format that allows for better decision-making. Data engineers are experts in various tools and techniques for wrangling data, such as extraction, transformation and loading (ETL).

  • Programming languages: Programming is a vital part of data engineering. Professionals in this field are typically familiar with some programming languages such as Python.

  • Data migration and integration: These professionals handle the task of aggregating data from multiple sources and moving it from one platform to another, depending on the demands of the business. Therefore, data engineers have knowledge of data migration and integration techniques, along with the tools necessary to accomplish them.

  • Cloud computing: With an increasing amount of data and the growing demand for more resources to process it, cloud computing is becoming a major part of companies' data infrastructure. Therefore, they rely on data engineers to create data solutions leveraging cloud providers.

Other differences between data architect and data engineer

These are some differences between the two professions:

Areas of expertise

Data architects typically serve as an intermediary between the IT sector and other departments. Translating business requirements into technical requirements enables them to define data principles and standards. Their typical work environment involves collaborating with people from other teams, such as data analysts and data scientists. They help with issues related to access, storage, collection and security of data.

Data engineers are responsible for harvesting a large amount of data and preparing it for data scientists to use. Making mechanisms and interfaces for the transmission of data and ensuring reliable access to it is part of their role.

Tools and technologies

A data architect is proficient in a wide range of data management tools, such as data warehousing, data modelling and ETL tools. Certain projects may require architects with expertise in the replication and tracing of data. The role of these professionals has changed over the last few years, becoming more focused on visualising rather than constructing frameworks. Therefore, it is necessary for data architects to be adept at query languages such as NoSQL and Spark.

In contrast, data engineers utilise the organisational data blueprints developed by the data architects to gather, organise and prepare data. Data architects analyse and provide guidance about how to handle data sources from the different databases, whereas data engineers implement the architecture created by the architects and make it available to other data professionals.

Daily tasks

Data architects focus on leading projects and developing high-level data strategies. They usually delegate tasks to the data management team and oversee their activities. The day-to-day tasks of data engineers include cleaning, gathering and preparing data for other users, such as data scientists and analysts.


The national average salary of a data architect is ₹13,92,457 per year. Through experience, they can advance to levels such as solution architect, enterprise architect and principal architect. The national average salary of a data engineer is ₹10,25,353 per year. Through experience, they can advance to levels that involve managerial roles or take up job roles such as data architect or machine learning engineer. These salaries can depend on several factors such as the employer, location, educational qualifications, experience and skills.

Related: Leadership Roles (With Examples And Functions Of Leadership)


Taking strategic business decisions requires the expertise of a data architect. Pursuing a career path in this field allows you to showcase your leadership qualities as you delegate tasks and work with the data administration staff to create a framework for an organisation's data. Additionally, you are responsible for implementing, coordinating and maintaining an enterprise-wide data architecture.

A career path in data engineering can be challenging and rewarding. Your role as a data engineer is crucial to the success of an organisation, as you make data more accessible to data scientists, analysts and decision-makers. You can develop scalable solutions by using your programming skills and problem-solving abilities.

Salary figures reflect data listed on Indeed Salaries at the time of writing. Salaries may vary depending on the hiring organisation and a candidate's experience, background and location.

Please note that none of the companies, institutions or organisations mentioned in this article are associated with Indeed.

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