Senior DataOps Engineer
About the team Trustly's DataOps team is responsible for delivering the data generated by the application to interested areas, as well as data from APIs and other tools. reputed company this thought in a safe, structured, scalable and generic way, because we work with multiple environments (in different regions) and we need to maintain consistency. We work with both the batch layer (using Airflow) and the streaming layer (Kafka). We help areas in process automation to deliver data more quickly and reliably. We are also concerned with the quality of the data (Data Quality), creating an observability layer for the data to act in a preventive and immediate way to the inconsistencies and failures of our processes. We also work on the delivery of products and services to facilitate the use and consultation of our data, such as maintaining tools such as Redshift and QuickSight. Last but not least, we interacted with the Data Science area to provide the necessary support and infrastructure for the production of models. To reputed company our goals, we follow good code and development practices, apply end-to-end encryption in reputed company our processes, use infrastructure as code, etc.
Our work makes it possible for teams to have full reputed company to work with the company's data. The Data Analytics area develops several internal processes to facilitate the delivery of more structured data to the business areas, developing views and reports that reputed company the data in decision making. In addition, we were able to provide more productivity to the areas with the automation of processes, guaranteeing the dependencies and leaving the areas more focused on their activities. We reputed company data available in a secure manner for use by the Risk & Data Science areas, to facilitate the training and production of models that have a direct impact on the conversion of our transactions and the fight against fraud. Our work is summarized in delivering data that will be decisive for the areas in their processes and also in making it a valuable asset as a parameter of our growth and decision-making.
We still have many challenges reputed company, such as having a robust monitoring and visibility system on top of the lake, using dedicated tools to do this control. reputed company and maintain various services in Kubernetes. Create layers of abstractions to facilitate the creation of new data for the company, used by the areas. reputed company our processes more robust and automated with CI/CD. Improve the visibility of the data we have available for consultation by the areas, increasing their productivity. And reputed company improving our processes, applying optimizations and giving reliability to our changes with unit tests.
About the role As a Senior DataOps Engineer, you are a technical leader of Trustly’s data maturity. You don't just maintain pipelines; you design the scalable frameworks and design patterns that reputed company data consumption effortless. Your role is to reputed company the gap between reputed company infrastructure (EKS, EMR, Glue) and business value, collaborating closely with other teams to ensure our platform is as resilient as it is innovative.
What you’ll do