
Number Theory is looking for experienced software/data engineer who would be focused on owning and rearchitecting dynamic pricing engineering systems
Job Responsibilities:
Evaluate and recommend Big Data technology stack best suited for NT AI at scale Platform
and other products
Lead the team for defining proper Big Data Architecture Design.
Design and implement features on NT AI at scale platform using Spark and other Hadoop
Stack components.
Drive significant technology initiatives end to end and across multiple layers of architecture
Provides strong technical leadership in adopting and contributing to open source technologies related to Big Data across multiple engagements
Designing /architecting complex, highly available, distributed, failsafe compute systems dealing with considerable scalable amount of data
Identify and work upon incorporating Non-functional requirements into the solution (Performance, scalability, monitoring etc.)
Requirements:
A successful candidate with 8+ years of experience in the role of implementation of a highend software product.
Provides technical leadership in Big Data space (Spark and Hadoop Stack like Map/Reduc,
HDFS, Hive, HBase, Flume, Sqoop etc. NoSQL stores like Cassandra, HBase etc) across
Engagements and contributes to open-source Big Data technologies.
Rich hands on in Spark and worked on Spark at a larger scale.
Visualize and evangelize next generation infrastructure in Big Data space (Batch, Near
Real-time, Realtime technologies).
Passionate for continuous learning, experimenting, applying and contributing towards
cutting edge open-source technologies and software paradigms
Expert-level proficiency in Java and Scala.
Strong understanding and experience in distributed computing frameworks, particularly
Apache Hadoop2.0 (YARN; MR & HDFS) and associated technologies one or more of Hive,
Sqoop, Avro, Flume, Oozie, Zookeeper, etc.Hands-on experience with Apache Spark and its
components (Streaming, SQL, MLLib)
Operating knowledge of cloud computing platforms (AWS,Azure) –
Good to have:
Operating knowledge of different enterprise hadoop distribution (C) –
Good Knowledge of Design Patterns
Experience working within a Linux computing environment, and use of command line tools
including knowledge of shell/Python scripting for automating common tasks.

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