Neeraj Kumar Singh

Developed and optimized data models using Gremlin-python and Amazon Neptune DB. Architected and implemented automated reporting pipelines on AWS using Terraform for Infrastructure as Code (IaC). Leveraged AWS services including Batch Jobs, ECR, S3, Glue Crawler, DynamoDB, Cognito, and Neptune DB to streamline data ingestion and processing workflows. Managed fine-grained access control and permissions using AWS IAM and Lake Formation.

Partnered with clients to understand business requirements and delivered tailored solutions for user data using AWS Cognito for secure authentication and DynamoDB for scalable data storage.

Designed and developed scalable, reusable, event-driven data pipelines to ingest sports data from multiple sources. Stored and managed processed and raw sports data in AWS Data Lake (S3), DynamoDB (NoSQL), and Redshift (DWH), while streaming real-time data using Kinesis Data Streams and MSK (Kafka). Utilized a broad range of AWS services, including Lambda, SNS, SQS, Kinesis, S3, CloudWatch, API Gateway, DynamoDB, AppSync, MSK (Kafka), Athena, Redshift, and Glue.

Developed event-driven data pipelines to ingest financial data from multiple sources. Stored processed and validated data in AWS S3 for scalable storage and DynamoDB for low-latency access. Utilized C# and Python for advanced data transformation.

Independently managed the entire product lifecycle for the Stock Trading Dealer Application for OMS. Integrated WebSocket APIs and REST APIs across multiple application modules. Developed new features and performed bug fixes for technical charts in Zerodha Pi.