What does Data engineer do and their 3 common roles?

role of a data engineer


Data Engineers are an integral part of any companies data analytics team. In contrast, data scientists are responsible for analysing and using the data for various purposes. To do this, they require excellent quality data. That is where a Data Engineer’s role comes in.

Role of a Data Engineer builds data channels that will transform raw, semi-structured and unstructured data into proper formats for data scientists to analyse. They are responsible for creating, optimising, monitoring, maintaining, and overseeing the analytics framework, allowing every other data function to work properly.

What is Data Engineering?

Data Engineering is the system of compiling and authenticating information that data scientists will use to analyse and build frameworks. Data Engineering focuses on the practical significance of data science and is one step ahead of simple data retrieval and analysis.

Who are data engineers?

Data Engineers are frontline warriors of the analytics department of any enterprise. They belong to the IT department of an organization. It is a job that requires a significant set of technical skills. These include proficiency in multiple programming languages such as Python, Java, R, a deep knowledge of database systems such as SQL and NoSQL, ETL tools, Machine Learning, Data Warehouse Solutions and Data APIs.

A data engineer requires technical skills and needs excellent communications skills to work across different departments of an organisation and understand the company’s/ client’s goals

What does an Engineer do on a typical day?

On Average a Data Engineer will spend their time on

  • Creating Frameworks.
  • Developing new data validation methods.
  • Writing accurate queries or ETL logic.
  • Sorting and Stitching data.
  • Determining and Evaluating New Data Sources.
  • Developing Data pipelines based on requirements.
  • Collecting Requirements for Data Models.
  • Managing Real-time Data and making sure it’s Secure.

This is not all that a Data Engineer does in a day neither do they perform every single task mentioned above every day. What the role of a Data engineer is will vary according to the company’s requirements or client.

What is the Role of a Data Engineer?

The Role of a Data Engineer is to find trends in massive data sets consisting of raw,

unstructured, and semi-structured data and to come up with efficient and effective algorithms for better access. They prepare and transform information. This includes extracting data from different source systems, transforming it and storing it into a data warehouse. This mechanism is known as ETL, that is Extract – Transform –Load. That is why data engineers are also sometimes known as ETL developers.

Data Engineer Roles and Responsibilities in layman terms is to manage data and data curation. They are also known as BI developers, technical architects, data science engineers, etc. Regardless of what they are called, these experts take the first pass at enormous amounts of information

that researchers, businesses, and government bodies access.

3 Common Role of a Data Engineer

According to Dataquest the 3 most common roles of a Data Engineer are:

  • Generalist:

These Data Engineers are usually found at Smaller sized organisations and are among the few ‘data focused’ people in the company. A Generalist must Manage as well as Analyse the data.

  • Pipeline Centric:

These Data Engineers are usually found at Mid-sized organisations, and they work alongside data scientists to analyse data. They require an in-depth knowledge of computer science and distributed systems.

  • Database Centric:

These Data Engineers are usually found at Larger organisations where they take no part in analysing the data as managing data is a full-time job. They work with data warehouses across multiple databases.


Data Scientists may make the headlines, but Data Engineers are the ones who make Data Science possible. They are the foundation of any organisation. Without them, a company would have no proper data to analyse or to work on. The Data Operations architectural framework gives support for management and environment creation, which helps develop and test the production environments that ultimately help in orchestrating, test automation, and monitoring


Himanshu Mishra

Technology Head
Himanshu is an entrepreneur with 17+ years of overall experience in strategic and advisory roles in Senior Management, IT program management, Quality Assurance, and ERP implementations. He has invested in companies focused on Digital Technologies and Healthcare industries. He has previously worked in domains like: Technology, Finance, Marketing, Media & Entertainment and Quality Assurance.

Passionate about technology, innovation, and music, he always keeps up with market trend…

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