Rakshith Lokesh

Software Engineer

Bengaluru, Karnataka, India2 yrs 5 mos experience

Most Likely To Switch

Key Highlights

Expert in building high-performance data pipelines.
Proficient in microservices architecture and implementation.
Strong background in data engineering and performance optimization.

Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in E-commerce and SaaS.

Contact

rakshithlokesha@gmail.com LinkedIn

Skills

Core Skills

Distributed SystemsMicroservicesData EngineeringSap Hana

Other Skills

ABAPAJAXAlgorithm AnalysisAlgorithmsAmazon Web Services (AWS)Apache KafkaArduinoBig Data Processing (Apache Spark,Hadoop)BootstrapCascading Style Sheets (CSS)Data StructuresDatabases(SQL,MongoDb)Devops(Docker,Kubernetes,Maven,Jenkins,Google Cloud Platform,CI/CD,ELK)Elastic Stack (ELK)Elasticsearch

About

Java, Spring Boot, distributed systems, microservice ,data engineering, and performance optimization At Flipkart, I build high-performance data pipelines and inventory backend services that have improved warehouse allocation Previously delivered scalable solutions at SAP Labs and Tekion. For anything, reach out at rakshithlokesha@gmail.com

Experience

Flipkart

SDE 1

May 2024 – Present · 1 yr 10 mos · Bengaluru, Karnataka, India

Building Flipkart Minutes

JavaSpring BootDistributed SystemsMicroservices

Sap

SDE 1

Oct 2023 – May 2024 · 7 mos · Bengaluru, Karnataka, India

Contributed to Dockerized microservice with Java, Apache Kafka, and Spring Boot to autonomously trigger dynamic superannuation calculations post-payroll execution.
Developed OData services in SAP HANA to expose data models as RESTful APIs
Integrated OData APIs with SAP Fiori and other UI applications, providing users with an interactive and responsive experience through real-time data updates

JavaApache KafkaSpring BootODataSAP HANAMicroservices

Tekion corp

Assistant Software Engineer Intern

Jan 2023 – Jul 2023 · 6 mos · Bengaluru, Karnataka, India

Developed and maintained a high-performance microservice for Elasticsearch support, creating wrapper classes and Feign clients to facilitate seamless integration with 10+ services.
Implemented optimized Redis key configuration and binary search techniques to enhance key-value retrieval efficiency and scalability for a microservice.
Implemented CRUD functionality for managing application configurations in a microservice-based config service. Successfully handled a database with 5,000+ records.
Achieved a 40% improvement in response times through effective optimization of database queries and utilization of MongoDB indexes.

ElasticsearchRedisMongoDBMicroservices