The advent of Data Science and Big Data has brought about the escalation of job roles in the Data Industry as there is an obsession about insights and deductions that can be generated from data being produced by small/large corporations to bolster their business acumen and as such, Data Scientists, Data Analysts, and Data Engineers are employed to unearth this valuable information.
Finding ways and methods to harness information is the duty of the Data Engineering team and specifically the ETL Engineer who is also known as the ETL Developer. The ETL Engineer uses specific tools and practices to implement methods in which data could be moved from multiple storage sites, transforming them to acceptable formats that would be used by others or machines, and then loading them to repository locations.
This process is known as Extract, Transform, and Load (ETL) which is the backbone of Business Intelligence (BI) as the data can not be used in its raw format to get actionable information and it is the sole responsibility of the ETL Engineer in a Data Engineering team to perform this duty.
This article is aimed at discussing the role of an ETL Engineer in the Data Industry, it will cover the key duties and responsibilities of an ETL Engineer, the required skills to become a successful one, and the type of educational qualification required.
Table of Contents
Introduction to ETL
ETL stands for Extract, Transform, and Load. These three processes are required to move data from one data source, multiple data sources or different types of data from diverse sources into a unified location often a Data Warehouse.
Understanding the Need of an ETL Engineer in Data Engineering
Data Engineering is the broad spectrum of the team issued with the responsibilities of obtaining raw data, developing infrastructures, building and testing the Data Pipelines to optimize a system for Analytical Purposes. The ETL Engineer usually known as the ETL Developer has the sole responsibility of being the one to perform the ETL process to build the Pipeline that will connect the raw data to the repository.
An ETL Engineer/Developer is an IT specialist who designs Data Storage Systems where data is stored to suit the requirements of the company. The ETL Developer is usually a Software Engineer that handles the Extraction, Transformation, and Loading data processes by developing infrastructures to do this efficiently. They also test and troubleshoot the system to ensure maximum performance.
The Data Engineering team is usually large and may comprise all or some of the following depending on the scope of the project to be executed by an enterprise:
- Data Architect
- Database/Warehouse Developer
- Database Administrator
- Data Scientists
- Business Intelligence Developer
- ETL Engineer
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Roles and Responsibilities of an ETL Engineer
ETL Engineers have a wide range of Roles and Responsibilities as they seek to design credible Data Storage solutions for companies, overseeing the ETL processes, and testing the system architecture. The Roles performed are listed below.
1) Determine the Data Storage Needs
The first thing an ETL Engineer should consider is to determine the exact storage needs of the organization as this will differ from one organization to another. You will need to have a clear indication of the current data situation of the organization and proffer the best possible solution that fits their requirements.
2) ETL Process Management
The next responsibility of an ETL Engineer is to ascertain the methodologies and technologies to deploy in creating the Data Pipeline and storage solutions for the organization as this is one of the key stages of Data Processing. To do this, you will state the requirements of the system and the entire ETL process by setting borders for Data Processing, determine the architecture for the Data Pipeline by defining each element in it, develop and implement ETL tools, conduct testing of the tools and Data Pipelines.
3) Data Modelling
This simply means deciding on the format your data will be when transferred to the Data Pipeline and the Data Warehouse. These formats are referred to as Data Models as they define the transformation stage and the technologies to be used in creating both the logical models and physical Database Structures. They are usually conceived and constructed through collaborations from various members of the team made up of Data Scientists, Data Analysts, Data Engineers, and Business Analysts.
4) Design & Create a Data Warehouse Architecture
One of the main responsibilities of an ETL Engineer is to design and create a Data Warehouse for an organization based on the determined needs of the firm. A Data Warehouse which by definition is a large storage facility used for the storage of Structured Data is subdivided into smaller parts known as Data Marts. Data Marts are helpful in meeting the specific requirements of units/departments that want to have access to data with unique properties in the Data Warehouse.
The ETL Engineer will have to define the Data Warehouse Architecture, tools used to load data into the Data Warehouse, how the end-users interact with the Data Warehouse, access information from it, manipulate it, make queries, and form Reports as well.
5) Development of Data Pipeline
At this stage, the ETL Engineer will construct a system that will extract data from a given source using various ETL tools that will integrate with the source locations, upload the data into the staging area where formatting will occur, formatting the data by cleansing it to delete unwanted Data Fields and Records, mapping and structuring of the data to define data types, and adding Metadata to it to meet the required standards. Finally, the Structured Data is then loaded to the Data Warehouse.
6) ETL Testing and Troubleshooting
After setting up the system, the ETL Engineer must test it to ensure that it is operating smoothly and fix any issue that may arise. Such system tests can be carried out by testing the unit Data Models, testing Data Warehousing Architecture, system performance test, uploading/downloading/querying speed test, Data Flow Validation, etc.
Skills Required to Become an ETL Engineer
An ETL Engineer despite it being a discipline-specific role must possess expertise in several fields ranging from Technical Skills, Analytical mindset, to good communication skills as this will be useful in seeing/meeting a company’s data situation and needs as well as communicating solutions to your client. The skill-sets needed to become an ETL Engineer are listed below:
1) ETL Tools/Software
ETL tools are used to Extract, Transform, and Load data into a Data Pipeline hence, an ETL Engineer must have vast knowledge and experience using them. These tools are used to create mappings, provide a graphical user interface for the Developer so you can see the entire workflow from the source to the target point as this will help you to integrate existing instruments with the ETL tools, manage the entire operations, and create a favourable interface for users to connect to the data whenever they want to use it. Industry-standard ETL Tools include Hevo Data, Talend, Informatica, and Pentaho.
2) Database Knowledge
An ETL Engineer should have a good knowledge of Database Engineering as this is the bedrock of Data Storage and Warehouse Architecture design. The most common Database Language used is Structured Query Language (SQL) and every part of ETL can be achieved using SQL as ETL tools can be regarded as SQL Generators. Knowledge of the NoSQL database is also required.
Experience using technologies like Hadoop and its components HDFS, SPARK, HBASE, Hive, Sqoop which can function as a framework and platform used for data integration can ease your workload as an ETL Developer. Other software to be conversant with as an ETL Developer are OLAP, SSAS, MDX, Java, and/or .NET. Modelling tools such as Toad Data Modeller, Edwin, and Embarcadero can also come in handy.
4) Scripting language
Dealing with Databases and moving data across locations will require you to have good Coding Skills as sometimes, you will need to input codes yourself to overcome challenges encountered to ensure an automated and smooth process. Popular scripting languages used for ETL are Python, Bash, and Perl.
5) Software Engineering Background
6) Analytic/Organization Mindset
ETL Engineers should have an analytical mind as this will help in the organization of jobs to perform at a given time. Arranging your workload into sections and knowing which to execute at a time can go a long way in keeping your data structured and ensure that your ETL mappings and workflows are created to run efficiently.
Situations will occur where everything does not go to plan and this will mean you have to troubleshoot or debug the entire system. An ETL Developer is saddled with this responsibility therefore, you have to be creative and come up with solutions to solve such problems whenever they arise.
8) Personal Qualifications
To be a successful ETL Engineer, you need to interface efficiently with your team members and management so you need good communication skills to understand their business requirements. You also need to have the ability to learn and adapt to new techniques and have good project management skills.
Educational Qualifications of an ETL Engineer
Typically, ETL Engineers mostly have Bachelor’s Degrees in Computer Science, Software Engineering, or related fields. BI/ETL Training Certificates such as Microsoft Certified Professional Certificate in MCSA: SQL BI Development, Informatica Certificates, etc. are also sought after by some.
ETL Developers/Engineers are needed in every company that works with Big Data as ETL cannot be separated from Big Data Management and Business Intelligence and this article brought to light the roles and responsibilities of an ETL Engineer and the requirements you will need to become one.
As there has been an explosion in the demand for data across the globe, so it has become imperative to have good ETL Engineers in any Data Operation, therefore, this article has given you the prerequisite knowledge for becoming an ETL Engineer/Developer and the role you will play when you successfully become one.
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