Kubernetes, Apache Ignite, Docker, Spring Boot, REST, Multithreading, Apache Cassandra, Scrum Methodology, Java, TDD methodology, Apache Kafka, PostgreSQL, Agile Methodology
Work with big volumes of data, timeseries data;
Develop functionality and services related to data analysis, aggregation, caching, diagnostic etc;
Build data flows to analyze big volumes of data;
Suggest improvements on algorithms currently used for data analysis;
Improve existing micro-services that are working with big data (we’ve just started the project, so mostly it’s about developing something new).
Luxoft team is developing a family of condition-based and predictive health management products that uses various online and offline data sources to provide preventive intervention recommendations based on grid asset condition, probability of failure, criticality and risk assessments. Data lake collects telemetrics data, makes clearance, manages archives. Rich UI to visualize results of analysis and diagnostics, prognostics, including 3D representation, builds prognosis on assets health and performance. Offline data is gathered via hybrid mobile application and through external connectors.
We are working with BigData scale and using latest technologies like Java 11, SpringBoot 2, Spring Clould, Kafka, Ignite, Cassandra, PostgreSQL, Jupyter, Docker and Kubernetes, AWS, Angular 10.
Our team is distributed between Ukraine and France (client), with a core team based in Dnipro.
Opportunities: participate in multi-year project for one of the biggest companies in the World and contribute to the platform that will change work experience and results of energy grid engineers across the globe.