Über
Data Engineer with experience in the development of data solutions in cloud environments, mainly on Azure. With solid knowledge in Databricks, Python, PySpark and Scala, focused on the construction, optimization and maintenance of ETL processes and data pipelines. Mastery of relational databases and advanced queries using SQL, PL/SQL and T-SQL. Experience working with Spark SQL, development of data engineering processes in the cloud, management of repositories through GitHub and continuous integration and deployment practices (CI/CD). Additional knowledge in BI/ETL tools as well as experience in cloud platforms such as AWS and/or GCP is valued. Responsibilities
Design, develop and maintain scalable data pipelines using Databricks, PySpark, Python and Scala. Implement extraction, transformation and loading (ETL/ELT) processes to integrate data from multiple sources. Develop and optimize queries, stored procedures and data models using SQL, PL/SQL and T-SQL. Manage and process large volumes of information in cloud environments, mainly on Microsoft Azure. Create and maintain notebooks, jobs and workflows in Databricks for efficient data processing. Ensure the quality, integrity and availability of data through automated controls and validations. Collaborate with analytics, BI and business teams to understand requirements and convert them into data solutions. Implement good development practices, version control and automation using GitHub and CI/CD tools. Job Requirements
Experience in Databricks (minimum 1 year). Experience in GitHub and CI/CD (minimum 1 year). Handling of Python, PySpark, Scala and Spark SQL. Mastery of SQL, PL/SQL and T-SQL. Experience developing data processes in Azure Cloud. Availability for a project of at least 6 months. Location: Latin America. English: Not required.
Sprachkenntnisse
- English
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