Who Is an ETL Developer?

An ETL Developer is an IT specialist, well-versed in software engineering and database development, who designs, develops, automates, and supports complex applications to extract, transform, and load data. ETL stands for “extract, transform, load.” It refers to the 3-step process of preparing raw data so that data analysts and data scientists can use it to gain actionable insights about the business.

Step 1: Extract

Organizations generate massive volumes of data. This data may be stored across multiple systems and in a wide range of different formats. Data must be extracted from cloud environments, CRMs, or other external systems before it can be used in applications or for analytics or machine learning.

Step 2: Transform

After data is extracted and collected, it’s in a raw state and needs work to make it compatible with defined standards. Transforming data can involve:

  • Cleansing: removing inconsistencies and missing values
  • Standardizing: bringing datasets into a required format
  • Deduplicating: excluding irrelevant data
  • Verifying: removing data that can’t be used and marking aberrations
  • Sorting: organizing data by type

Step 3: Load

The final step is to load transformed data into data storage, such as a data warehouse, cloud data warehouse, cloud data lake, or data lakehouse, or into external systems or applications. These systems include automated tools to make data accessible for users, such as business intelligence tools for visualizing and reporting on data.

What Are the Responsibilities of an ETL Developer?

ETL Developers must have a big-picture view of their organization’s data needs and environment and are responsible for a wide range of duties and tasks.

  • Determining Data Storage and Management Needs: ETL Developers figure out the exact storage needs of the organizations they work for. ETL Developers need a clear, detailed picture of their organization’s current and future data architecture, environment, and needs.
  • Designing and Building Data Storage and Management Systems: ETL Developers design systems, such as cloud data warehouses, cloud data lakes, or lakehouses, to address their organizations’ data needs and work with development teams to build them.
  • Building Data Pipelines: ETL Developers create and manage data pipelines—that is, reliable tools and processes that deliver data to end users—to connect to data in different formats and move it between systems.
  • Extracting, Transforming, and Loading of Data: When building data pipelines, the goal of an ETL Developer is to extract data, prepare it, and move it —in full loads and/or incremental data loads— from a source file into a destination, such as a cloud data warehouse, cloud data lake, data lakehouse, or external application.
  • Testing and Troubleshooting: ETL Developers perform quality assurance tests to make sure their systems and pipelines are stable and run smoothly. ETL Developers also identify and resolve system problems that may arise within the warehousing system.

How Does Alteryx Designer Cloud Help ETL Developers?

Alteryx Designer Cloud significantly reduces the time, technical skills, and costs required for ETL Developers to access any type of data, wherever it resides, and automates the process of transforming data and building data pipelines.

The Designer Cloud helps ETL Developers transform data, ensure quality, and automate data pipelines, making data consumable at any scale. This intelligent, collaborative, self-service data engineering cloud platform helps ETL Developers:

  • Connect to data from any source. With universal data connectivity and a self-service architecture, Designer Cloud makes it fast and easy for ETL Developers to connect data from any source. This makes it easier for ETL Developers to support a wider range of data integration use cases and applications.
  • Transform raw data into ready-to-use data. ETL Developers can use Trifacta’s visual interface and predictive data transformation suggestions to greatly reduce the time it takes to detect and resolve complex data patterns and transform them into consumable data across the organization.
  • Create real-time previews of transformed data. Designer Cloud presents automated, visual, and interactive representations of data. ETL Developers can use these previews to explore data more deeply and understand it at its most granular level. Outliers in the data can be automatically identified and flagged for follow-up, helping ETL Developers easily eliminate bad data.
  • Build, automate, and deploy data pipelines. With just a few clicks, Designer Cloud helps ETL Developers build automated data pipelines at scale. With Designer Cloud, ETL Developers can deploy and manage self-service data pipelines in minutes, not months.