Shivansh Narayan

Software Engineer

Bengaluru, Karnataka, India4 yrs 7 mos experience

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Key Highlights

Led technical merger of auto-complete feature with zero downtime.
Developed efficient ML feature ingestion pipeline reducing update time.
Built scalable backend systems for diverse applications.

Stackforce AI infers this person is a Backend Engineer with expertise in SaaS and EdTech solutions.

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Skills

Core Skills

Backend DevelopmentData Pipeline EngineeringMachine LearningWeb Development

Other Skills

AWSAWS Sage-MakerAirflowApache-SparkApplication Programming Interfaces (API)Back-End Web DevelopmentDatabasesDesign PatternsDockerElastic-SearchExpressJsJavaJenkinsKafkaLeadership

About

As a Software Engineer-II at OYO, I design and develop backend systems and data pipelines across search and personalisation ecosystems, using ElasticSearch, Kubernetes, Kafka, and machine learning. I have a BE in Information Technology from the Birla Institute of Technology, Mesra, where I graduated in June 2021. I have led and contributed to several impactful projects at OYO, such as the technical merger of the auto-complete feature of Belvilla(Oyo's European Business) into the Global OYO Stack, the framework for type-ahead suggestions for multilingual search, and the efficient data pipeline for updating the features for ML models. I have also participated in a college-level hackathon by Microsoft and a summer program by Crio.Do, where I enhanced my skills in data structures, algorithms, and system design. I am motivated by solving challenging problems and creating impactful solutions. I value collaboration, learning, and innovation, and I can bring diverse perspectives and experiences to the team.

Experience

Greenlight

2 roles

Software Engineer 2

Feb 2025 – Present · 1 yr 1 mo

Software Engineer

Oct 2023 – Feb 2025 · 1 yr 4 mos

Oyo

3 roles

Software Development Engineer-II [Search and BFF]

Jul 2023 – Oct 2023 · 3 mos

Designed the event ingestion and search prediction pipeline with new widget creation for a user person-alised home-page . Estimated impact of 3 mil $ / month
Ingestion pipelines handles 1.4 million events /day. Using a fire-and-forget design with a P99 of
5ms (MongoDB,Spring-Boot,Thread-Pools)

MongoDBSpring-BootThread-PoolsBackend DevelopmentData Pipeline Engineering

Software Development Engineer-I [Search and Ranking]

Aug 2021 – Jul 2023 · 1 yr 11 mos

Autocomplete Migration ->
Led the technical merger of the auto-complete feature of Belvilla into the Global OYO Stack without downtime while coordinating with the business and product team to tune the algo for desired relevance.
Built framework for type-ahead suggestions for multilingual search (6 languages)
The system manages the indexing, relevant searching and updates of 0.6 million locations
ML-Feature Ingestion Pipeline ->
Developed an efficient data pipeline for updating the features to be used by ML models. Integration of new features reduced from 3 days to a couple of hours
The pipeline handles feature updates for models catering for India, Indonesia and Malaysia. Feature updates per day are about 9 million (Elastic-Search, Kafka, Apache-Spark)
Ranking MLOps Platform ->
We developed and deployed infra for a one-click data preparation and model training/analysis pipeline. Reducing dev effort from 10 days to 3 days and daily cost from 250$ to 150$ (Spark, Airflow, AWS Sage-Maker, Jenkins).
Other Projects: gRPC POC, Spark on K8 POC, Listing Page Widgets

Elastic-SearchKafkaApache-SparkData Pipeline EngineeringMachine Learning

Software Development Intern [ML Engineer - Ranking]

Feb 2021 – Jul 2021 · 5 mos

Global Search and Rank Team

Edulyx

Software Development Intern

Apr 2020 – Dec 2020 · 8 mos

Assessment Feature :
1. This feature allowed teachers to schedule and create assessments on the platform.
2. There were many pre-defined question types along with an intuitive UI for ease.
Exam-Engine :
1. This service was built to conduct the scheduled assessments.
2. Features include -> session management, Auto Save, Auto Submit, Server Side Timekeeping
Correction-Module :
1. Module for the correction and report generation/analysis of Submitted assessments.
2. This also included a dashboard for the teachers to see the data and its distribution.
The System was designed in a way that Assessment Creation, Submission, Checking, Data Analysis happened in an Asynchronous manner.
Tech-Stack: ExpressJs , ReactJS , Redux , RabbitMQ , AWS , Docker , Nginx , MongoDB

ExpressJsReactJSReduxRabbitMQAWSDocker+3

Crio.do

Student Developer

May 2019 – Jun 2019 · 1 mo

In Crio Summer Of Doing, student developers build real products in a work-like environment called Micro-Experience, set up by Crio.Do
I have built a distributed system backend for food order platform, QEats, with Java Spring Boot and MongoDB.
My Project and Skill summary can be viewed from the link below
https://criodo.github.io/csod-2019-narayanshivansh49/#CSOD