Piyush Patel

About Piyush Patel

Senior Software Engineer with 10+ years of experience designing and building distributed, cloud-native systems for financial services, e-commerce, and healthcare platforms. Specialized in Python-based backend engineering, microservices architecture, large-scale data processing, and cloud infrastructure automation, with strong expertise in designing systems that handle high-throughput APIs, asynchronous workflows, and data-intensive applications. Extensive experience building production-grade backend systems using Python (FastAPI, Django, Flask, AsyncIO) and designing high-performance REST and gRPC APIs supporting large-scale distributed services. Skilled in implementing event-driven architectures using Apache Kafka, Redis Streams, Celery, and message queues, enabling scalable asynchronous processing pipelines for transaction processing, analytics workloads, and real-time system integrations. Strong background in database architecture and data processing, working with relational and distributed data stores including PostgreSQL, MySQL, MongoDB, Cassandra, DynamoDB, and Redis. Experienced in designing optimized query strategies, indexing models, caching layers, and high-performance data pipelines using SQLAlchemy, Pandas, NumPy, and PySpark for large-scale data transformation and analytics. Hands-on experience developing machine learning and AI-driven backend services, implementing data preprocessing pipelines, model inference services, and intelligent automation workflows using Scikit-Learn, TensorFlow, and LLM-based retrieval architectures (RAG) to support advanced analytics and knowledge retrieval systems. Deep experience building cloud-native applications and infrastructure automation using AWS and Azure cloud platforms, working with services such as EC2, EKS, S3, RDS, DynamoDB, Lambda, CloudWatch, Azure AKS, Blob Storage, and Azure Functions to design highly available, fault-tolerant systems. Strong DevOps and platform engineering background with experience implementing CI/CD pipelines using GitLab CI, Jenkins, GitHub Actions, and container build pipelines, supporting automated testing, artifact management, and zero-downtime deployments. Implemented observability and monitoring frameworks using Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana), and distributed tracing systems, enabling real-time monitoring, performance analysis, and incident diagnostics across distributed systems.

Experience

1. Senior Software Engineer

   BNY

   Mar 2023 — Present · Manhattan, NY, US

   Working on enterprise cloud modernization initiatives focused on building distributed financial platforms, cloud-native microservices, and high-throughput data processing pipelines for internal banking systems.• Architected and implemented high-performance microservices using Python (FastAPI, Django, AsyncIO) with containerized deployments using Docker and Kubernetes, supporting scalable financial services applications.• Designed and developed RESTful and asynchronous APIs using FastAPI, gRPC, and OpenAPI specifications• Built event-driven processing pipelines using Apache Kafka, Redis Streams, and Celery task queues, enabling asynchronous execution of transaction validation, compliance checks, and financial data enrichment workflows.• Designed optimized data access layers using PostgreSQL, SQLAlchemy ORM, and Redis caching, implementing indexing strategies, query optimization, and connection pooling to improve API performance and reduce database latency.• Developed distributed data processing workflows using Python, Pandas, NumPy, and PySpark, enabling large-scale financial data transformation, reconciliation, and analytics.• Implemented machine learning–driven enrichment workflows using Scikit-Learn and TensorFlow supporting intelligent anomaly detection and financial risk analytics pipelines.• Migrated legacy monolithic services to microservices architecture deployed on Kubernetes clusters (EKS) with container orchestration, horizontal scaling, and service discovery.• Implemented infrastructure automation using Terraform, Helm, and Kubernetes manifests, enabling consistent infrastructure provisioning and environment configuration across dev, staging, and production environments.• Built CI/CD pipelines using GitLab CI, Jenkins, Docker build pipelines, and Kubernetes • Integrated enterprise authentication systems using OAuth2, JWT, OpenID Connect, and RBAC security policies, ensuring secure access to internal APIs and financial services.

Education

• Gujarat Technological University (GTU)

  Python and SQL Crash cources, Python and SQL Crash cources

  2012 — 2012