- Strong experience with Hadoop and its ecosystem in design, development and implementation.
- Strong experience in working on Apache spark using scala. Insights into data search ( Solr/Elasticsearch ) and data processing in Hadoop/big data environment.
- Writing high-performance, reliable and maintainable code in languages like scala and python.
- Track record of working on perform analysis of vast data stores and uncover insights while maintaining the security and data privacy
- Exposure to automotive domain will be an added advantage
- The CS fundamental concepts like data structures ( array, list, map, tree ), memory management, parallel processing, OOps concepts should be checked very thoroughly.
- Apache spark development in Scala ( scala is a programming language called salable language ) is the MUST. The candidate needs to have a strong understanding on scala concepts including data structures/collections, functional/OO programming aspects
- Depth of experience of what the person has worked on and what kind of problem he has solved. Generic data loading in Hive ( it's a big data component ) and minimalistic transformations using spark will not work for client.
- Handling the huge data volume and understanding the performance bottlenecks in big data system.
- High speed and data volume search using any open source technology like solar, elasticsearch based on lucene.
Salary: Not Disclosed by Recruiter
Industry:IT-Software / Software Services
Functional Area:IT Software - Application Programming, Maintenance
Role Category:Programming & Design
Employment Type:Permanent Job, Full Time
Desired Candidate Profile
Fluid AI works with the global banks and Corporates provide AI experience. Fluid AI provides the AI experience on Mobiles with 15 million interactions. Fluid AI believes that the power of artificial intelligence can be used across industries, sectors and use cases. Our team is working hard to bring about a future where our solutions redefine the landscape of what is possible using AI.
View Contact Details+