Abdhesh Kumar

Expedia-SDE-III - Scala | Spark | Kafka | Kotlin at Expedia Group, London

Seasoned Software Engineer with over 12 years of experience in designing and developing scalable, cloud-native microservices and big data applications.
Proficient in building high-performance systems using Scala, Spark, and Kafka, with deep expertise in reactive programming and distributed systems.
At Expedia, led the development of gRPC and GraphQL microservices in Kotlin, Java and Spring Boot while delivering robust streaming solutions using Kafka, Reactor, and Kafka Streams.
Demonstrated strong command over modern architectures, including event sourcing, CQRS, and cloud-based deployments, with a proven track record of reducing system latency and improving throughput in mission-critical environments.

Programming Languages & Web Technologies: Scala, Akka, Cats/Cats-effect, Http4s, Circe, ZIO, ES6-Javascript, Java, fs2, Protobuf, gRPC, pure-config.
Big data: Hadoop, Spark, MapReduce, Hive, Hbase, Kafka
Tools/Frameworks & Cloud:AWS, Git, Jenkins, Docker, Kubernetes, Agile, Scrum, Spring Boot**, Cloud Computing
Databases: Mysql, Hbase, MongoDB, Redis, Cassandra, Dgraph, DynamoDB

M.C.A(Master of Computer Applications) from Dr. A.P.J. Abdul Kalam Technical University, India in 2011.
B.Sc.(Maths) from Dr. Bhimrao Ambedkar University, India in 2008.

Engineered gRPC/GraphQL full stack applications in Scala/Kotlin/Java with Spring Boot for the Personalisation Platform, leveraging AWS cloud services to enhance scalability and deliver personalized travel experiences.
Outlined technology stacks including Kotlin/Java, Spring, gRPC, Arrow-Kt, Protobuf, Kafka, Cassandra, and Datadog (Monitoring & Tracing) to ensure robust service performance.
Developed gRPC services in Scala for the Incentive Platform that boosted traveller engagement through efficient distributed microservices.
Utilized Scala, Cats, Cats-effect, ZIO, Cassandra, MongoDB, Elasticsearch, and Spark to create data-driven solutions, aligning with modern cloud computing practices.
Optimized service response time by reducing latency by 40% through the implementation of parallelized downstream service calls.
Constructed reactive streaming applications using Kotlin and Reactive Streams to support dynamic data flows in cloud-based environments.
Designed and developed Spark and Flink applications in Scala for large-scale data processing, integrating cloud computing approaches where applicable.
Architected and deployed a loyalty tier upgrade system using Kotlin and Kafka Streams, resulting in a 25% increase in app downloads within three months post-launch.

Designed and developed backend architecture of a reactive application
Designed Event Sourced CQRS system following the DDD approach backed by Akka Persistence using Cassandra Journal and Kafka. Using functional libs Cats and ZIO.
Designed a data processing system that processes the events emitted by entities.
Designed an Enrichment System to perform write-time joins.
Designed a serialisation layer using Google Protocol Buffers for Schema Evolution
Reduce call graph processing time from 1.5 min to 0.5 sec.
Replaced an existing system by new design to achieve vertical and horizontal scalability

Develop services to harvest reviews/feedback from sources and social data
Develop service to translate data, apply NLP and then persist reviews/feedback
Improve Legacy Code and provide new Architecture process 1.2 million/sec reviews
Providing Code-refactoring suggestions/Documents