Spark/Scala/Python Data Engineer

About Luxoft
Luxoft, a DXC Technology Company (NYSE: DXC), is a digital strategy and software engineering firm providing bespoke technology solutions that drive business change for customers the world over. Acquired by U.S. company DXC Technology in 2019, Luxoft is a global operation in 44 cities and 23 countries with an international, agile workforce of nearly 18,000 people. It combines a unique blend of engineering excellence and deep industry expertise, helping over 425 global clients innovate in the areas of automotive, financial services, travel and hospitality, healthcare, life sciences, media and telecommunications. DXC Technology is a leading Fortune 500 IT services company which helps global companies run their mission critical systems. Together, DXC and Luxoft offer a differentiated customer-value proposition for digital transformation by combining Luxoft’s front-end digital capabilities with DXC’s expertise in IT modernization and integration. Follow our profile for regular updates and insights into technology and business needs.
​​​​​​​Luxoft Romania has been established since 2001. We currently have approximately 2500 employees working from different locations in the country.

Experience in implementations of end-to-end data processing chains, Big data architectures (Hadoop cluster, noSQL databases, Elastic search) mastering languages ​​and frameworks for distributed data processing (Spark / Scala).
• Basic knowledge and interest in the development of ML algorithms
• Knowledge of the ingestion framework
• Knowledge of Spark and its different modules
• Mastery of Scala and / or Python
• Knowledge of the AWS or GCP ecosystem
• Knowledge of the ecosystem of NOSQL databases
• Knowledge in the construction of APIs of data products
• Knowledge of Dataviz tools and libraries
• Popularization of complex systems
• Expertise in data testing strategies
• Strong problem solving, intelligence, initiative and ability to withstand pressure
• Excellent interpersonal skills and a great sense of communication (ability to go into detail)

During project definition
• Design of data ingestion chains
• Design of data preparation chains
• Basic ML algorithm design
• Data product design
• Design of NOSQL data models
• Design of data visualizations
• Participation in the selection of services / solutions to be used according to the uses
• Participation in the development of a data toolbox

During the iterative realization phase
• Implementation of data ingestion chains
• Implementation of data preparation chains
• Implementation of basic ML algorithms
• Implementation of data visualizations
• Using ML framework
• Implementation of data products
• Exposure of data products
• Setting up NOSQL databases
• Implementation in distributed mode of treatments
• Use of functional languages
• Debugging distributed processes and algorithms
• Identification and cataloging of reusable elements
• Contribution on data processing problems

During integration and deployment
• Expertise in the implementation of end-to-end data processing chains
• Mastery of distributed development

Contribute to the business value of data-oriented products based on Datalake on-premise or cloud environments, by implementing end-to-end data processing chains, from ingestion to exhibition APIs and data visualization.
As responsibilities, you will maintain the high quality of data transformed in the Datalake, smooth operation of the data processing chains and optimization of the use of the resources of the on-premise or cloud clusters.