Data Engineer : Mastercard

Interview : Video Visa : USC, GC, GC EAD, H4, L2 This is hybrid from day-1. Onsite Day 1 - In office three days per week and in '24 they will move to four. Currently they are doing M/T/W in office, Th/F remote Description : Experience dealing with large volumes of data, from various sources, both structured and unstructured. Ability to triage and talk through performance / scaling issues of dealing with data at scale. Good understanding of how data will be read (file formats, partitioning, bucketing). Extensive experience writing testable jobs using Spark (or equivalent) framework. Programming & Scripting Languages: Java EE, Scala, Spark, SQL, Bash. Web services & API standards: REST, OAuth, JSON. Software Architectures (micro-services, event driven, peer-to-peer). Application Security. Asynchronous Pub-Sub and Point to Point Messaging Systems. Advantage, if you have experience working in ETL and Hadoop Ecosystem: HBase, Solr, Spark Streaming, Kudu, Spring Boot, Spring Context, Spring Data Rest, General Cloudera experience. Streaming within the Hadoop ecosystem is a plus.

Created: 2026-03-04