Vivek Bansal

Senior Software Engineer

Bengaluru, Karnataka, India5 yrs 3 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

5 years of experience in scalable application development.
Expertise in AWS and data engineering for high-performance systems.
Passionate about system design and enhancing user experience.

Stackforce AI infers this person is a SaaS-focused Software Engineer with strong expertise in data engineering and cloud technologies.

Contact

Skills

Core Skills

AwsData Engineering

Other Skills

AWS CloudWatchAWS SQSAlertingAlgorithm AnalysisAlgorithm DesignAlgorithmsAmazon EC2Amazon S3Amazon SQSAmazon Web Services (AWS)Apache SparkApache Spark StreamingC (Programming Language)C++C/C++ STL

About

I am a Software Engineer with 5 years of experience in building scalable, high-performance applications that deliver real impact. I thrive on solving complex engineering challenges, designing reliable distributed systems, and creating features that enhance user experience and engagement. Currently, I contribute to the development of the Camera application using Android and Java. I have delivered features which have helped significantly in improving app performance, ratings, and user satisfaction. I hold a B.Tech in Software Engineering from Delhi Technological University and am passionate about continuous learning, system design, and building products that delight end users.

Experience

Samsung electronics

Senior Software Engineer

Sep 2022 – Present · 3 yrs 6 mos · Bengaluru, Karnataka, India

Publicis sapient

Associate Software Development Engineer 2

Nov 2020 – Aug 2022 · 1 yr 9 mos · Gurugram, Haryana, India

Designed and implemented an end-to-end pipeline to consume customer records from AWS SQS and ingest them into Cassandra, ensuring high throughput and scalability.
Built a custom retry mechanism for failed records, improving reliability and reducing message loss in production workloads.
Developed monitoring and alerting using AWS CloudWatch, with automatic escalation via Dead Letter Queues (DLQ) and email notifications, ensuring faster resolution of data pipeline failures.
Optimized ingestion flow for large-scale data, enabling real-time processing of millions of customer records with high availability.
Collaborated across teams to improve system resilience, fault tolerance, and operational visibility in a mission-critical customer data platform.

AWS SQSCassandraAWS CloudWatchData PipelineHigh ThroughputScalability+5