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.