Vetted D3.js Professionals

Carlotta Island

Screened ReferencesStrong rec.

Junior Frontend Engineer specializing in React and FinTech web applications

3y exp

“Developer who uses AI as a practical collaborator rather than a crutch, pairing tools like Claude with console logging, testing, and hands-on validation. They emphasize understanding code, data flow, and architecture while staying current by building projects and following AI and engineering communities.”

Preetham Dandu

Screened ReferencesModerate rec.

Junior Software Engineer specializing in backend, distributed systems, and cloud platforms

Stony Brook, NY1y exp

“MS candidate with strong backend/data engineering focus who builds research and data systems with production-grade rigor (reproducibility, observability, restartability). Has hands-on experience securing and scaling FastAPI-based gateways in front of Java microservices, leading SQL Server→Snowflake migrations with dual-write/feature-flag rollouts, and hardening Kafka-based fleet-tracking systems against out-of-order and duplicate events.”

“Frontend engineer who led an enterprise customer-facing analytics dashboard end-to-end, handling complex visualizations, real-time updates, and high-performance requirements. Demonstrates strong architecture and scale practices across React/TypeScript, Redux Toolkit/RTK Query, GraphQL, and performance techniques like virtualization and code-splitting, plus disciplined QA/rollout with feature flags, Cypress, Sentry/New Relic, and Lighthouse.”

“Full-stack engineer from Vagaro who owned an end-to-end rebuild of a sluggish WordPress sales site into a Next.js 15 app hosted on Azure, adding Hygraph headless CMS, SSR, i18n, and a reusable component library. Instrumented Amplitude + A/B testing/heatmaps and reports a 10% sales lift post-launch; also has AWS ops experience (S3/IAM/CloudWatch) and has built ingestion pipelines including LLM-powered unstructured data processing with dead-letter handling.”

“Customer-facing software engineer who rapidly turns business requirements into Figma prototypes and PoC applications, using workflow prioritization and frequent client reviews to stay aligned. Has hands-on experience integrating with existing authentication/user APIs, building MongoDB-backed caching, and implementing robust fallback/retry mechanisms. Comfortable working on-site with customers and resolving production issues in AWS (e.g., DNS/EC2 traffic routing) in collaboration with DevOps.”

“Robotics/embedded candidate who built an IoT smart shoe for visually impaired users, implementing real-time obstacle detection with ultrasonic sensors and haptic feedback on Arduino. Has practical ROS experience (RViz/Gazebo) and improved reliability in distributed systems by hardening an Arduino-to-ROS serial protocol with framing, strict parsing, and sensor-noise filtering; also containerized ROS environments with Docker for reproducible simulation and onboarding.”

“ML/NLP engineer (Beyond Identity) who built production semantic search and entity-resolution systems over internal security documentation, using LDA + BERT embeddings with FAISS/Pinecone to cut search time by 30%. Also scaled a real-time anomaly detection pipeline to millions of events/day with Spark and AWS Lambda, with strong emphasis on measurable validation (Precision@k, MRR, F1, ARI).”

“Full-stack engineer who built an end-to-end low-code/no-code IDE for creating AI/ML workflows for industrial IoT sensors using Next.js/TypeScript and NestJS microservices. Focused on scaling high-volume sensor dashboards—improved UX and performance via WebSockets, debouncing, pagination, and API payload reduction—validated with profiling tools and user feedback in a startup environment.”

Sivapriya Rachakonda

Screened

Mid-Level Software Engineer specializing in cloud-native microservices on AWS and Kubernetes

Remote, USA5y exp

“Backend engineer who built a stateless Python/Flask service supporting a healthcare-document ETL pipeline, offloading heavy processing to Celery workers and adding strong observability (metrics, structured logs, audits). Demonstrates practical performance/reliability work: batch chunking, priority queues, autoscaling by queue depth/CPU, DLQ routing, and PostgreSQL tuning (indexes, pagination) to cut slow API responses. Also has experience deploying real-time ML classification via TensorFlow Serving behind a FastAPI wrapper and integrating models via REST/gRPC.”

Rahul Solleti

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and full-stack web apps

United States5y exp

“Backend/platform engineer focused on real-time financial fraud detection and transaction monitoring, building low-latency FastAPI + Kafka systems with strong reliability patterns (DLQs, idempotency) and cloud observability. Has hands-on Kubernetes delivery across AWS EKS and Azure AKS with automated CI/CD and GitOps-style deployments, plus experience migrating legacy C# / Java monoliths to containerized microservices using Terraform/ARM and zero-downtime rollout strategies.”

“Full-stack engineer with experience building customer-facing fintech mobile features end-to-end (loan estimate comparison) and scaling event-driven microservices in enterprise environments (Verizon). Has designed TypeScript/React/Node systems with queues/caching and built an internal rule-engine for bulk Excel ingestion that reduced data errors and manual rework through automated validation.”

“Built a production LLM-RAG system at McKesson to let internal healthcare operations teams query large volumes of unstructured operational documents via natural language with source-backed answers, designed with HIPAA/FHIR compliance in mind. Demonstrated strong production engineering across hallucination mitigation, retrieval quality tuning, and latency/scalability optimization, using LangChain/LangGraph and Airflow plus rigorous evaluation/monitoring practices.”

“Product-focused full-stack engineer (Spring Boot/Django + React/TypeScript) with deep experience building multi-tenant, enterprise workflow and supply-chain/order-tracking systems. Owned an end-to-end Workflow SLA Breach Prediction & Alerting feature integrating Azure ML for a cloud workflow platform used by ~10,000 enterprise users, and has hands-on AWS operations experience resolving real production latency/scaling incidents via query optimization and Redis caching.”

“Backend/data engineer focused on production Python and AWS: built FastAPI REST services and a containerized ECS Fargate + Lambda architecture deployed via Terraform/CI-CD. Strong in data engineering (Glue/S3/Parquet/RDS) and operational reliability (CloudWatch/SNS, retries, schema-evolution handling), with experience modernizing legacy SAS reporting into Python microservices using feature flags and parity validation.”

“Full-stack engineer who has owned React/TypeScript + Spring Boot dashboard products end-to-end, including real-time performance/alerts and data aggregation across services. Strong in shipping MVPs quickly with feature flags, automated testing and CI/CD, and using monitoring/click-path analytics to prioritize work—achieved a 40% page-load reduction. Experienced operating microservices with RabbitMQ at scale, addressing retries/idempotency/observability and fixing duplicate-processing incidents with idempotent consumer patterns and DLQs.”

Kavya Myakala

Screened

Mid-level Frontend Developer specializing in security analytics dashboards

NJ, USA4y exp

“Built and shipped production LLM agents including an end-to-end customer support resolution system (99.9% uptime target) that improved customer satisfaction by ~18% and reduced the need to scale support headcount. Demonstrates strong agent engineering fundamentals—tool-based orchestration, schema-first structured outputs with deterministic validation, and robust eval/monitoring loops—plus experience integrating agents with messy ERP data using canonical normalization and safe fallbacks.”

Ido Avnon

Screened

Junior Software Engineer specializing in AI, geospatial, and full-stack applications

Seattle, WA5y exp

“Early-stage startup engineer with experience at pre-seed and roughly Series A-stage companies, including Rage Events Inc. Shipped production full-stack features with Next.js/TypeScript, designed Postgres-backed workflow systems, and took ownership of post-launch support and fixes in fast-moving environments.”

“Enterprise implementation/deployment specialist focused on HRMS and payroll systems across APAC customers, combining cloud/hybrid (AWS/Azure/GCP) integration work with strong client-facing delivery. Demonstrated ability to debug complex production issues across application, database, and network layers (e.g., isolating VPN/router congestion) and to tailor Python-based data cleaning/scoring/utilities to customer-specific workflows.”