January 28, 2026
In the modern world, data is considered the new oil and data obsession is all the rage, as all businesses struggle to get information. But, gathering data is worthless unless you can make sense of it.
Used for various purposes such as performing analytics or creating machine learning models, but data can’t be applied in its raw format. Any system dealing with data processing requires moving information from storage and transforming it properly. Usually this process is carried out by an ETL Developer full form which stands for Extract, Transform, Load.
In this article, we will discuss “What is ETL Developer”, responsibilities, ETL Developer skills, and ETL Developer job description.
What is ETL Developer?
ETL Developer full form stands for Extract, Transform, and Load. An ETL developer is a software engineer who manages the Extract, Transform, and Load processes, implementing technical solutions for these operations.
ETL Pipeline
To move data from one system to another, an ETL developer builds a specific data pipeline that covers the Extract, Transform, and Load stages.
- Extract: Businesses store historical information or stream real-time data into many systems. This information is scattered across different software and is structured in various formats. The extraction phase involves defining required data sources and gathering data from them.
- Transform: When the data is gathered, it is usually placed in a temporary storage area called a staging area. In it, the data is formatted according to defined standards and models.
- Load: The final stage of an ETL process is loading the structured and formatted data into a database.
How Does an ETL Developer Work?
An ETL developer’s work follows a structured process that turns raw data into analytics ready information. While the topic of what is ETL tool and its usage may vary, the overall workflow is generally consistent.
Here is how an ETL developer’s work is usually structured:
Gather Requirements
Collaborate with business and technical teams to understand data sources, rules, and reporting needs.
Profile Source Data
Analyze the structure, quality, and constraints of each source system.
Design the Pipeline
Define how data will be extracted, transformed, and loaded into the target environment.
Build ETL Workflows
Develop repeatable processes using ETL tools, scripting languages, or automation platforms.
Apply Transformations
Clean, standardize, enrich, and reshape data to meet business and reporting requirements.
Validate and Test
Ensure data accuracy, completeness, and performance through testing and automated checks.
Deploy and Schedule Pipelines
Operationalize workflows so they run reliably and at the right cadence.
Monitor and Optimize
Track performance, address data quality issues, and refine workflows as systems evolve.
What is ETL Tool?
ETL Tools are software solutions that orchestrate and automate the entire ETL Process. In general, what is ETL Tool is a simple query because they share the similar workflow of Extracting data from source systems, transforming it, and then loading the data into a target system.
What is ETL Tool: Comparison
| Azure Data Factory | Fully managed serverless data integration service that can be used to create ETL pipelines. |
|
| AWS Glue | AWS-based managed serverless data integration service with support for both visual and code-based interfaces. |
|
| Xplenty | A cloud-based scalable ETL service to create ETL pipelines. |
|
| Hevo | A no-code data pipeline platform to create real-time data integration pipelines. |
|
| Matillion | Cloud data integration and transformation platform with a comprehensive toolset to create ETL pipelines for any enterprise need. |
|
| Informatica PowerCenter | An enterprise-grade ETL tool offering a wide range of data integration capabilities. |
|
What is SQL?
SQL (Structured Query Language) is a powerful programming language. It’s mainly used to manage and communicate with databases. It is the standard language used in most relational database management systems (RDBMS).
There are some of the most common SQL commands:
- SELECT: This command allows you to select data in a database.
- WHERE: It is used to apply conditions to the SELECT statement to filter your results.
- ORDER: This command allows you to sort results in either ascending or descending order.
- JOIN: This command joins related data stored in different tables to retrieve combined results.
- ALIAS: It is used to give table a temporary nickname that’s more easily readable.
- INSERT: This command lets you add new data to an existing table or database.
ETL With SQL: How They Work Together
While both are distinct, ETL with SQL are often used together in data management. Here’s how:
ETL with SQL: Extract
- SQL is used to define the query that will extract the data from the external source systems.
- Queries can also be used in this phase to filter data, perform calculations, and join tables before the data is extracted by ETL tools.
ETL with SQL: Transform
- The data transformation phase allows analysts to convert unstructured data into packaged data sets. This is where SQL does the heavy lifting.
- During transformation, SQL functions like COUNT, SUM, and AVG are used to summarize data by grouping rows.
ETL with SQL: Load
- In the final phase of the ETL process, SQL is used to define the schema of the target system.
- From there, it can be used to create tables and indexes, optimize queries, and even enforce referential integrity.
ETL Developer vs Data Engineer
What is ETL developer? How is it different from a Data Engineer? These questions are often raised. Of course, a data engineer can combine his and an ETL developer job description in a small company, but if we are talking about a large team and a huge amount of data, it makes sense to hire separate performers for these positions.
An ETL developer job description mainly includes data integration and building ETL pipelines to convert the data into required format and move it from the original source to the destination system. Their typical workday may involve writing code, though not necessarily. Sometimes, it’s enough to master ETL tools that have a graphical interface.
Data engineers, on the other hand, solve more strategic problems by dealing with the overall data ecosystem, big data technologies, and cloud computing. They design, build, and optimize systems to collect, store, scale, access, and analyze data.
A data engineer may also perform management duties, lead teams, and assign projects to ETL developers. Therefore, a data engineer can be the next career step for an ETL developer.
Conclusion
While ETL developers may not be the most talked-about path in data careers, they remain one of the most practical and reliable entry points into the data ecosystem. Their expertise in data integration, transformation, and management remains essential for achieving successful data initiatives and driving business growth.
Ready to leverage ETL Developer skills for your business? Take the first step today and hire an ETL Developer from Logix Built Solutions Limited. Our expert team helps empower your growth with custom and efficient solutions designed especially for you.
Frequently Asked Questions
Q1: What is an ETL Tool that most developers work with?
Many ETL Developers work with ETL patterns, cloud data platforms, APIs, and Python-based workflows, depending on the organization’s architecture.
Q2: Does an ETL developer job description include having coding skills?
ETL developers often do need coding skills, but at varying levels.
Q3: What is the relationship between data warehousing and ETL?
ETL is the process that feeds data into a data warehouse. They both work together to ensure clean, structured data is available for reports, dashboards, and business analysis.
Q4: What are the most important ETL Developer skills in 2026?
SQL expertise, Python programming, cloud-platform familiarity, understanding ETL/ELT approaches, data-quality and governance principles, and experience with modern tools like Airbyte.
Q5: Is ETL development a good career choice given the rise of ELT?
Yes. Many enterprises still require ETL for compliance, legacy systems, and specific transformation needs. ETL developer skills translate well to broader data-engineering roles.