Minimum Qualifications

• Good in communication
• Bachelor degree in Computer Science, Information System or related field
• At least 1 year of working experience in ETL Developer
• Required skills: SQL/Database Oracle, ETL Tools
• Good communication and fast learner
• Excellent problem-solving skills

Preferred Qualifications

• 3 years working experience as  ETL Developer
• Experience with data processing tools : Spark, Kafka, Cloudera
• Experience with data visualisation tools : Tableau and Power BI

About this job

Our company has a need for ETL Developer, an ETL Developer is an IT specialist who designs data storage systems for companies and works to fill that system with the data that needs to be stored. ETL stands for “extract, transform, load,” which is the process of loading business data into a data warehousing environment, testing it for performance, and troubleshooting it before it goes live. ETL Developers must be experts at taking a big-picture view of a company’s data situation to come up with comprehensive data storage solutions. In our company ETL Developer is responsible for designing and creating the data warehouse and all related extraction, transformation and load of data functions.  This means data needs to be copied, or extracted, from businesses processes and loaded into the data warehouse so all of the information is up-to-date. The job role might also require you to learn new tools and technologies fast, and you should have in-depth database knowledge as well as basic programming and scripting skills. You will help to build efficient and stable data pipelines which can be easily maintained in the future.

Job Responsibilities

• Design, Develop and Test ETL Mappings, Mapplets, Workflows, Worklets to support business requirements.
• Perform feasibility, impact analysis and suitable solutions based on the use cases
• Ensuring data management and governance to maintain the data integrity
• Develop data mappings to extract the data from XML/Database and loading to the source stating database tables
• Create shell scripts for ETL purpose
• Maintain and improve already existing processes
• Ensure that the data architecture is scalable and maintainable