Kartikay T.
About Me
Senior Full Stack Engineer with 6+ years of experience in building scalable data platforms, Al/ML pipelines, and cloud-native backend systems using Python, AWS, and Databricks. Strong expertise in end-to-end ML lifecycle, including data ingestion, feature engineering, model-ready dataset preparation, deployment support, and monitoring. Hands-on experience with AWS services (S3, Glue, Lambda, Step Functions, Kinesis, ECS/EKS, SageMaker) for building distributed and serverless architectures. Skilled in event-driven architectures and streaming pipelines using Kafka/Kinesis for real-time data processing. Proficient in backend/API development using Django, FastAPI, and Flask for building scalable data services and ML model endpoints. Experience with CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps) and infrastructure as code using Terraform for automated deployments. Strong expertise in SQL optimization, data warehousing, and Lakehouse architecture (Databricks, Delta Lake). Proven experience in ML model deployment, monitoring, and performance tracking in production environments. Experienced in debugging production issues, optimizing pipelines, and ensuring SLA-driven execution. K. has developed scalable backend services using Python, Django, and FastAPI for automation and AI/ML workflows, built serverless and event-driven pipelines using AWS Lambda, Step Functions, and Kinesis. Designed REST APIs for billing, invoicing, and ML data services. Supported AI/ML pipelines by preparing feature-ready datasets and validation frameworks. Implemented monitoring using AWS CloudWatch for alerting and debugging. Worked on CI/CD pipelines (Jenkins, GitHub Actions) and Terraform (laC). Optimized SQL queries and data pipelines for performance and SLA compliance.
