Daman Singh, Developer in Ghaziabad, India
Daman is available for hire
Hire Daman

Daman Singh

Verified Expert  in Engineering

Back-end Developer

Ghaziabad, India
Toptal Member Since
May 6, 2022

For the past five years, Daman has been working as a back-end developer, building B2B and B2C applications. Some industries he's worked in include retail, supply chain, and fintech. Daman's most notable experience was working on building and scaling complex microservices for business functions, including KYC/KYB, authorization, ledger flows, and integration testing. He loves to code in Go and believes it's built for software engineering today.


Go, gRPC, REST, OAuth, Amazon Web Services (AWS), PostgreSQL...
Amazon India
Java, Big Data, Serverless, Natural Language Processing (NLP)...




Preferred Environment

Amazon Web Services (AWS), Go, Google Cloud Platform (GCP), Back-end, Linux, Algorithms, Microservices

The most amazing...

...project I've worked on was mapping geocodes to physical activity (walking, running, driving, etc.) with 80%+ precision, using simple ML and ad-hoc algorithms.

Work Experience

Senior Back-end Engineer

2021 - 2022
  • Developed high-throughput, low-latency APIs and coped with distributed and highly concurrent environment challenges as part of the core platform back-end team.
  • Helped the recruiting process by interviewing potential candidates and deciding on anyone who would be a good fit for the team.
  • Created and scaled multiple microservices. Implemented reliable async workflows for notifications and webhooks.
Technologies: Go, gRPC, REST, OAuth, Amazon Web Services (AWS), PostgreSQL, Amazon Quantum Ledger Database (QLDB), Amazon Simple Queue Service (SQS), Amazon Kinesis, Microservices Architecture, Microservices, Scalable Architecture, REST APIs, RESTful Web Services, RESTful Microservices, Prometheus, Grafana, Amazon CloudWatch, Kubernetes, Gin-Gonic, Viper, Rancher, Docker, GitHub, APIs, Containerization, Software Architecture, Technical Leadership

System Development Engineer (BIE)

2018 - 2021
Amazon India
  • Developed RESTful APIs, integrated with third-party services, and designed and managed relational and NoSQL databases.
  • Built highly scalable and fault-tolerant event-driven architectures using AWS Kinesis to handle high-volume data processing and real-time analytics.
  • Decomposed and migrated legacy software from EC2 to multiple other AWS services, including serverless, ECS with Fargate, API gateway, etc.
Technologies: Java, Big Data, Serverless, Natural Language Processing (NLP), Amazon S3 (AWS S3), Go, Microservices, REST APIs, Python, ETL, Algorithms, Kubernetes, APIs, Software Architecture, Technical Leadership

Real-time Data Processing and Analytics Platform

The system consisted of several microservices written in Go and deployed using Amazon Elastic Container Service (Amazon ECS) with Fargate as compute resource. The microservices were responsible for tasks such as data ingestion, processing, and visualization.

AWS Kinesis was used as a distributed streaming platform to handle real-time data streams and ensure fault tolerance and scalability. The data was ingested into the platform using Kinesis producers and consumed by microservices for processing and analysis.

The platform incorporated real-time concurrency handling techniques like channels and mutexes to ensure thread-safe access to shared resources and prevent race conditions.

The platform also had a web-based dashboard that displayed real-time analytics, such as charts and graphs, based on the data ingested.

Real Estate Portolfio Management Platform

The platform allows users to add any property owned within the UK. It displays multiple trends (historical and forecast), including price, rentals, etc., and comparisons with district and city-based benchmarks.

As part of my role, I:
• Developed the entire back end using Go and multiple AWS services like RDS, DynamoDB, SQS, SageMaker, Lambda, EKS, etc.
• Used Terraform to manage and version control infrastructure and GitHub actions for CI/CD.
• Created and fine-tuned the low latency address autocomplete feature for a dataset of millions of addresses using a combination of Postgres indexes.
• Built a reliable async workflow to run ML predictions using SQS and SageMaker.
2014 - 2018

Bachelor's Degree in Engineering

Birla Institute of Technology and Science, Pilani - India


Stripe, REST APIs


Auth0, GitHub, Amazon Simple Queue Service (SQS), Amazon CloudWatch, AWS Fargate, GitLab CI/CD, Jenkins, Kibana, Slack, GoLand, Amazon EKS, Amazon Elastic MapReduce (EMR), Grafana, NGINX, Docker Compose, Amazon Elastic Container Service (Amazon ECS), Amazon SageMaker


gRPC, Swagger, Gin-Gonic, Viper, JSON Web Tokens (JWT)


Go, Python, SQL, Scala, Java, Python 3, Bash


REST, Microservices Architecture, Microservices, DevOps, Linear Programming, Concurrent Programming, Object-oriented Programming (OOP), ETL


Kubernetes, MacOS, Docker, Amazon Web Services (AWS), Apache Kafka, Rancher, Visual Studio Code (VS Code), AWS Lambda, Amazon EC2, Google Cloud Platform (GCP), Linux


MongoDB, Amazon S3 (AWS S3), Redshift, PostgreSQL, Amazon DynamoDB


OAuth, Amazon Quantum Ledger Database (QLDB), Amazon API Gateway, APIs, Webhooks, Serverless, Scalable Architecture, RESTful Web Services, RESTful Microservices, Containerization, Stripe Payments, WebSockets, Software Architecture, Technical Leadership, Big Data, Amazon Kinesis, Natural Language Processing (NLP), Clustering, Prometheus, Schemas, Distributed Systems, Computer Science, Algorithms, Data Structures, Operating Systems, System Design, Generative Pre-trained Transformers (GPT), Back-end, Amazon RDS, Multitenancy, Audio, Audio Processing

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.


Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring