Architecture and development of actor-based clusters, implementation and maintain of custom rule-engine using functional Scala approach. Development of data pipelines (Spark, Kafka, Azure Data Factory) deployed on Microsoft Azure and based on Azure dev-Ops ecosystem.

On Inventory:

Akka cluster – for support of rule engine, written on Scala on functional style, event sourcing patter, command state pattern.

Bit data part is all rule engine data input – there are streaming jobs (Spark structure streaming), Microsoft Azure Data Factories, Azure Functions, data in blobs, there is Kafka (message broker, dirstibuted message log), Kafka connect.

There is SQL – in out Oracle, Postgres, planned migration to SpliceMachine

Threre onsite systems on customer side – onprem oracle – data factory grabs and puts to PostgreSQL at HAVI – then via kaffka connect to rule engine to Akka cluster (first cluster enrichment, then other to other cluster).

Desired requirements:

Theory of algorithms, algorithmic complexity
Functional development approach – major requirement
Non-blocking IO, asynchronous approach
Actor based frameworks (Akka, Lagom, Lightbend in general)
Actor topology architecture, implementation.
Akka-Cluster, Akka-Http
Unit testing in all of the above.
Inventory systems domain expertise is a big plus.
Python knowledge is a plus.
Agile development methodology.

About EPAM


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