Vetted SQL Query Optimization Professionals

“Backend/API engineer with ~4 years experience building production services in .NET Core/PostgreSQL/Redis/Docker and optimizing real-world latency issues (claims ~60% response-time improvement). Also built and owned an end-to-end RAG-based AI assistant using Python/FastAPI, OpenAI APIs, and Pinecone, plus agentic workflows with reliability guardrails (retries, confidence thresholds, monitoring). Currently pursuing a master’s degree and targeting a $150k base salary.”

“Data engineer focused on production-grade pipelines and data services: ingests millions of records/day into S3, performs SQL/Python quality validation and PySpark/SQL transformations, and serves curated datasets via Athena/Redshift. Has experience hardening external data collection with retries/rate-limit handling and shipping versioned internal data APIs with backward compatibility, monitoring, and CI/CD in early-stage environments.”

“Data/ML platform engineer with healthcare (Cigna) experience owning an end-to-end pipeline spanning Airflow + Debezium CDC ingestion, PySpark/SQL transformations, rigorous data quality gates, and feature-store/API serving for ML training and inference. Worked at 10+ TB scale and cites a ~30% latency reduction plus stronger reliability via idempotent design, monitoring, and backfill-safe reprocessing; also built pragmatic early-stage data pipelines at Frankenbuild Ventures.”

“LLM/agent engineer with production experience in the insurance claims domain, integrating OpenAI + LangChain into a claims platform to automate unstructured document extraction/classification and cut manual effort by 35%. Built reliable, fault-tolerant AWS/Kubernetes microservices with CloudWatch monitoring plus circuit breakers/retries/fallbacks, and implemented multi-step Spring Boot orchestration with schema validation, confidence gating, and human-in-the-loop handling for low-confidence cases.”

“Data engineer/platform builder who has owned production pipelines end-to-end processing millions of records/day, with strong emphasis on data quality (quarantine workflows) and reliability (monitoring, retries, incremental loads). Also designed large-scale external data collection/crawling with anti-bot handling and backfills, and shipped versioned REST data services optimized for performance and developer usability in an early-stage environment.”

Saniya Shinde

Screened

Mid-level Data Scientist specializing in NLP, LLMs, and RAG systems

Washington, DC4y exp

“Built and deployed a production-style vision-language pipeline that generates structured medical reports from chest X-rays using BioViLT embeddings, an image-text alignment module, and BiGPT fine-tuned with LoRA, delivered via Streamlit and hosted on AWS EC2. Also collaborating experience presenting EDA findings, feature importance, and model performance to Ford managers while working with vehicle parts data at Bimcon.”

Sri Chandana Topuri

Screened

Mid-level Java Full-Stack Developer specializing in Spring microservices and Angular

5y exp

“Backend-focused engineer working primarily with Python/Django who also handles full-stack responsibilities. Has hands-on experience deploying containerized Python/Java microservices to Kubernetes using Helm and GitOps (ArgoCD), plus building Kafka-based event streaming with reliability controls (acks, consumer groups, DLQ). Also supported major on-prem to cloud/hybrid migrations using Terraform/Ansible with blue-green cutovers and data replication to minimize downtime.”

Saicharitha Yanamandala

Screened

Mid-Level Software Developer specializing in Java, Cloud, and Microservices

Chicago, IL6y exp

“Backend/Python engineer who owned an end-to-end FastAPI + AWS internal natural-language document Q&A system (Textract extraction, embeddings/vector DB, LLM integration) with strong focus on reliability and latency. Hands-on with Kubernetes + GitOps (Argo CD, Helm, rolling updates/auto-rollback) and built/optimized Kafka streaming pipelines using Prometheus/Grafana. Also supported a zero-downtime on-prem to cloud migration with parallel run and gradual traffic cutover.”

Kiran M

Screened

Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and data platforms

Bentonville, AR5y exp

“Backend/ML integration engineer with experience at Accenture and Walmart building Flask-based analytics and prediction APIs on PostgreSQL/MySQL. Strong focus on performance and scalability—uses precomputed aggregates, Redis caching, query tuning (indexes/partitioning/EXPLAIN), and async/background processing; also designs secure multi-tenant isolation with JWT and schema/db-per-tenant strategies.”

Shruthi Nandakumar

Screened

Mid-level Full-Stack Developer specializing in FinTech and cloud-native microservices

St. Louis, MO5y exp

“Backend/AI engineer who owned a high-scale Java/Spring Boot microservice for a financial application (millions of requests/day) and led major reliability/performance fixes (including ORM/query and PostgreSQL tuning) achieving ~60% latency reduction. Also shipped application-layer LLM features for ops teams (summarization + tool-calling) with strong guardrails (PII redaction, validation, audit/feedback) and designed a state-driven agent workflow with retries, circuit breakers, and human escalation.”

Nikitha Margadi

Screened

Mid-level Data Engineer specializing in cloud lakehouse, streaming, and MLOps

Texas, USA5y exp

“Data engineer at AT&T focused on large-scale telecom (5G/IoT) data platforms, owning end-to-end pipelines from Kafka/Azure ingestion through Databricks/Delta Lake transformations to serving analytics and ML. Has operated at very high volumes (~50+ TB/day) and delivered measurable performance gains (25–30% faster processing) plus improved reliability via Airflow monitoring, robust data quality checks, and resilient external data collection patterns (rate limiting, retries, dynamic schemas).”

Krishnamraju Penumatsa

Screened

Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines

Fort Worth, TX6y exp

“Data engineer currently at American Airlines who built and owned end-to-end flight operations and booking data pipelines (batch + real-time) using Azure Data Factory, Kafka, Spark/Databricks, Synapse, and Snowflake—processing hundreds of GBs/day. Strong focus on reliability and data quality (idempotency, checkpointing, retries, validation/alerts) and delivered near-real-time analytics powering Power BI dashboards; previously helped stand up an early-stage data platform at Sysco on AWS (Glue/S3/Redshift) with Airflow and Jenkins CI/CD.”

“Healthcare-focused data analyst with hands-on experience at Molina Healthcare building SQL and Python workflows for retention and churn analytics. They combined enrollment, CRM, and claims data into Power BI reporting, automated predictive churn analysis, and tied their work to measurable outcomes including faster processing, better reporting accuracy, and reduced churn.”

Udirno Chaudhuri

Screened

Mid-level Data Analyst and Product professional specializing in FinTech and AI applications

Santa Cruz, CA4y exp

“Payments/product-focused operator with hands-on experience owning complex bank connectivity deployments at Paystand, including a migration that raised connection success from under 50% to 79%. Also built a production-grade multi-agent document intelligence system on AWS Bedrock for structured enterprise document extraction, combining real-world fintech domain pain points with modern LLM architecture.”

Brendan Dwyer

Screened

Senior AI/ML Engineer specializing in GenAI and cloud platforms

Colorado Springs, CO10y exp

“ML/AI engineer with hands-on experience turning research-style RAG concepts into production underwriting systems at Prudential Financial. Built an internal document intelligence assistant end-to-end with strong monitoring, safety, and evaluation practices, driving a 38% faster review process and 31% better retrieval accuracy. Also improved platform engineering at VivSoft by standardizing Python-based ML deployment across 60+ models.”

Paavani Karuturi

Screened

Junior Backend and ML Engineer specializing in distributed systems and LLM infrastructure

San Jose, CA2y exp

“Backend engineer with strong ownership across authentication, API infrastructure, and AI-powered document workflows. They built and operated a production auth microservice supporting 10,000+ users with measurable latency and security improvements, and also shipped hackathon and applied-AI systems including legal document and medical document retrieval/Q&A products.”

Sai Sreenath Kalva

Screened

Mid-level Full-Stack Software Engineer specializing in AI and Healthcare IT

Rosemead, CA5y exp

“Full-stack engineer with strong AI architecture experience in regulated healthcare environments, including a HIPAA-compliant conversational reporting assistant for LA County Department of Public Health and clinical workflow features for Oracle Health/Cerner PowerChart. Stands out for combining LLM/RAG system design, healthcare compliance, and production-grade reliability practices across Azure, AWS, and Kubernetes.”

“Software engineer with 4 years of experience spanning scalable backend systems, full-stack product development, and production LLM integrations in finance, insurance, and e-commerce contexts. They describe shipping an AI-powered internal financial analysis tool, improving document-review workflows by 40%, and driving a zero-to-one B2B SaaS subscription launch with cross-functional GTM alignment.”

“Healthcare analytics candidate with hands-on experience turning messy claims and clinical data into validated SQL/Python pipelines and Power BI dashboards. They have delivered measurable impact in revenue cycle operations, including 15-18% improvement in reimbursement accuracy and 40-45% reduction in manual reporting effort.”

“Backend engineer in healthcare data systems who has owned production pipelines end-to-end, from ingesting patient and claims data to serving it through secure APIs. Brings a strong mix of Python, SQL, microservices, cloud deployment, and data reliability practices, with measurable performance gains and experience building resilient integrations with external data sources.”

“Frontend-leaning full-stack engineer with experience building real-time, high-stakes operational software for airport gate management and billing/analytics systems. Stands out for combining strong React/TypeScript architecture with backend and data-layer ownership, including WebSockets, SQL optimization, and analytics feature delivery in production.”

“Full-stack engineer focused on AI-powered enterprise document automation, especially transforming unstructured financial documents into structured outputs. Stands out for treating LLMs and agents as components within robust production systems, with emphasis on validation, security, observability, and scalable multi-agent architecture.”

“Backend engineer with hands-on ownership of Spring Boot microservice deployments in Freddie Mac's mortgage workflow domain, including measurable gains in reliability and MTTR. Brings strong production debugging skills around distributed transaction pipelines and has also built a full-stack AI chatbot project using React, Express, and Google Gemini API.”

“Backend engineer with experience at HSBC and Machinations who has delivered major production performance wins (cutting large trade-file upload times from ~13–15s to ~2s) using chunked parallel processing with strong reliability controls. Also built and shipped an applied AI RAG workflow using Langflow + Cohere embeddings + FAISS with hosted/local LLM fallbacks (Hugging Face, Ollama) and production-grade guardrails, observability, and evaluation.”