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Vetted Spring Data JPA Professionals

Pre-screened and vetted.

LS

Mid-Level Full-Stack Software Engineer specializing in Java/Spring and .NET

Dallas, TX3y exp
Goldman SachsUniversity of Texas at Arlington
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CK

Mid-level Backend/Distributed Systems Engineer specializing in cloud-native data pipelines

3y exp
NVIDIASanta Clara University
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GG

Mid-Level Software Developer specializing in FinTech and AI-enabled systems

Conroe, TX5y exp
McKinsey & CompanyBinghamton University
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MN

mahesh narne

Screened

Senior Full-Stack Software Engineer specializing in cloud-native microservices and web apps

San Jose, CA3y exp
PayPalUniversity of Central Missouri

Backend-focused engineer building customer support/order-tracking platforms with Java 17/Spring Boot microservices and a React/TypeScript frontend. Deep experience running event-driven systems on Kubernetes (Kafka, Redis, MySQL) with strong observability (Prometheus/Grafana/Splunk), SLOs, and safe deployment practices (feature flags, canaries). Also built an internal monitoring/debugging dashboard that consolidated metrics and logs for on-call engineers and was adopted by other teams to speed incident response.

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KC

Senior Full-Stack Developer specializing in cloud-native microservices

Dallas, TX3y exp
Bank of AmericaUniversity of North Texas

Bank of America engineer/product owner who built a real-time transaction insights and spending categorization platform using React/TypeScript and Spring Boot microservices with Kafka. Deep experience in event-driven architectures, performance tuning at peak banking loads, and reliability patterns (SLOs, observability, feature flags, DLQs). Also created an internal monitoring/alerting tool adopted across engineering and ops, cutting incident response time by 40%+.

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SM

Mid-Level Full-Stack Software Engineer specializing in Java, Spring Boot, and cloud microservices

4y exp
Capital OneCalifornia State University, Long Beach

Frontend-focused JavaScript engineer who built Collabsync with real-time chat and file sharing using Socket.io, emphasizing reusable components, clear event contracts, and performance (minimizing React re-renders). Has experience at PwC building internal React/Angular dashboards and documenting insurance APIs, plus a contract role at Capital One delivering in fast-changing, loosely defined environments.

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SR

Mid-Level Full-Stack Software Engineer specializing in microservices and fraud detection

Texas, USA4y exp
PayPalUniversity of North Texas
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KS

Mid-level Frontend Software Engineer specializing in React and cloud-integrated web apps

Los Angeles, CA5y exp
WalmartUSC
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AY

Intern Full-Stack Software Engineer specializing in cloud microservices and AI applications

Sunnyvale, California2y exp
Walnut.aiUSC
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VK

Mid-level Software Engineer specializing in backend systems and LLM-powered AI applications

San Francisco, CA6y exp
Twist BioscienceUniversity of Texas at Arlington
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EX

Junior Backend Engineer specializing in cloud-native systems and observability

Sunnyvale, CA2y exp
WalmartNYU
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SG

Mid-level Java Developer specializing in Spring Boot microservices (FinTech & Healthcare)

5y exp
PNCPace University
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MG

Mid-Level Software Engineer specializing in Java microservices and cloud-native systems

USA4y exp
CitigroupArizona State University

Full-stack engineer (SAP Labs experience) who built an end-to-end, real-time fraud detection system on Java 11/Spring Boot microservices with Kafka event streaming and a React/Redux analytics dashboard with WebSocket updates. Demonstrated strong production ownership by diagnosing a critical memory leak with Prometheus/CloudWatch + heap dumps and improving performance with Redis caching (40% faster queries), while also modernizing deployments via Kubernetes, Jenkins CI/CD, and Terraform.

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NP

Navya Panyala

Screened

Senior Software Engineer specializing in identity, cloud-native microservices, and reactive web apps

Bentonville, AR6y exp
WalmartUniversity at Albany

Product-focused full-stack engineer with Walmart and Dell experience who built and shipped a real-time engagement dashboard end-to-end (Kafka Streams, Spring Boot, React/TypeScript/D3) used daily by business teams, moving them from next-day reports to real-time decisioning. Strong in performance/reliability (Redis caching cut latency ~40%, 90%+ test coverage, Prometheus/CloudWatch monitoring) and production operations on AWS/EKS including handling a cascading failure from a memory leak with zero-downtime rollback and redeploy.

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MK

Senior Full-Stack Software Engineer specializing in microservices and cloud-native systems

New York City, NY4y exp
JPMorgan ChaseUniversity of Dayton

Backend/infra engineer with experience across Nestle, J.P. Morgan, and Capgemini, combining ML systems work (YOLOv8/PyTorch object detection with TFLite edge deployment) with production-grade cloud/Kubernetes operations. Has delivered measurable impact via AWS migrations (25% cost reduction, 99.9% availability), microservice modernization (35% faster processing), and low-latency Kafka streaming for financial dashboards (<100ms) using DLQs and idempotent consumers.

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JB

Jhansi Bendi

Screened

Senior Software Engineer specializing in cloud-native microservices and event-driven systems

Antioch, CA18y exp
SephoraRashtriya Sanskrit Sansthan

Senior engineer/tech lead with 18+ years building large-scale distributed applications, specializing in performance and reliability improvements. Recently owned multiple apps on an email personalization team, shipping major optimizations (including a push-update feature and audience-count architecture redesign) that reportedly lifted system performance from ~50% to ~99% while also leading code standards, reviews, and mentoring.

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KL

Krishna Lella

Screened

Mid-level Full-Stack Developer specializing in FinTech platforms

New York, NY4y exp
PayPalSt. Francis College

Product-focused full-stack engineer who built and shipped subscription/billing features end-to-end (FastAPI + React/TypeScript), including a self-serve cancellation flow with save-offers that reduced support tickets and improved churn insights. Experienced operating on AWS (ECS/EC2, RDS, S3/CloudFront) and handling real production scaling incidents through DB/query optimization, idempotent API design, and strong observability practices.

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