We are a leading trading platform that is ambitiously expanding to the four corners of the globe. Our top-rated products have won prestigious industry awards for their cutting-edge technology and seamless client experience. We deliver only the best, so we are always in search of the best people to join our ever-growing talented team.
As a Data Engineer, you will play a crucial role in our data team, contributing to developing and maintaining data pipelines and systems. You will work closely with data scientists, analysts, and other stakeholders to ensure the availability and reliability of data for decision-making and analytics. Your responsibilities will encompass data ingestion, transformation, and delivery, as well as maintaining and optimizing data infrastructure.
The Data Engineer is expected to contribute to developing and maintaining data infrastructure, ensuring data reliability and availability. You should be able to work independently and as part of a team, adapting to changing data needs and collaborating with data professionals to provide valuable insights to the organization. Staying current with data engineering best practices and emerging technologies is essential for success in this role.
The Data Engineer will design, develop, and maintain data pipelines and quality systems to enhance RTV's analytics and machine learning capabilities, directly impacting programmatic reach.
As a Mid-level Data Engineer, you will transform and model data, connecting business needs to reliable data sources ready for analysis within a multidisciplinary team.
As a Mid-level Data Engineer, you will design and build data pipelines, ensure data quality, and integrate databases for inference services while automating workflows.
Own and evolve the core data ingestion and transformation platform to ensure reliable data architecture, enabling critical functions to make real-time financial decisions.
As a Data Engineer - Spark Developer, you will design and improve data pipelines, utilizing Apache Spark and Azure services to create robust big data architectures.
