Mid-level Data Engineer – Big Data / Spark

Mid-level Data Engineer – Big Data / Spark About the opportunity We are looking for a Mid-level Data Engineer to work on the development, maintenance, and optimization of data processing solutions on the Client Contribution platform. The professional will be responsible for building scalable pipelines, ensuring data quality, and contributing to the evolution of the Big Data architecture in an agile environment guided by good engineering practices. Responsibilities Develop, maintain, and optimize data processing solutions; Design and develop ETL and data transformation processes; Implement and maintain pipelines using Apache Spark; Support data integration initiatives between different systems; Analyze and resolve data-related incidents; Ensure the quality, performance, and reliability of data solutions; Work closely with multidisciplinary teams in an Agile environment. Mandatory requirements Minimum of 3 years of experience in Data Engineering and development; Solid knowledge in SQL, including: ANSI SQL; Hive SQL; Spark SQL; Experience with Apache Spark; Knowledge of at least one of the following languages: Scala; Python; Java; Experience with Big Data platforms, such as: Azure Databricks; Amazon EMR; Hive; Cloudera; or another Spark-based environment; Experience with Qlik Sense for developing reports and dashboards; Experience in Continuous Integration (CI), DevOps environments, and methodology