vineetha Pulipati

About

Backend engineer with Morgan Stanley experience building and owning an end-to-end Python FastAPI microservice for high-volume market data used by trading and risk systems. Strong in performance tuning and reliability (PySpark, Redis caching, async APIs), real-time streaming with Kafka, and production operations (Docker/Kubernetes, GitOps-style CI/CD, monitoring). Has led cloud/on-prem migration work across AWS and Azure, including fixing Azure Synapse performance issues via query and pipeline redesign.

Experience

Education

Key Strengths

• Owned end-to-end backend microservice architecture and implementation (FastAPI market data service)
• Performance optimization across ingestion and API layers (PySpark parallelism, batching, async endpoints, reduced serialization overhead)
• Built resilient data normalization layer to handle inconsistent provider formats
• Designed scalable real-time streaming consumers (parallel consumer groups, increased partitioning) to handle peak market-open spikes
• Implemented data quality controls in streaming (schema validation, quarantine/fallback logic)
• Production deployment expertise with Docker/Kubernetes, autoscaling (HPA), and monitoring (CloudWatch/K8s metrics)
• Planned and executed cloud/on-prem migrations with Terraform, parallel run validation, rollback planning, and minimal downtime focus
• Resolved post-migration data warehouse performance issues (query rewrites, partitioning, incremental loads, caching)