Vetted SQL Query Optimization Professionals

Srilekha Jakkula

Screened

Senior Data Engineer specializing in scalable data pipelines and API-driven data services

Chicago, IL5y exp

“Data engineer focused on building scalable, reliable end-to-end data pipelines and backend REST data services, spanning API ingestion plus batch/stream processing with Airflow, Kafka, Spark/PySpark, and SQL. Emphasizes strong data quality validation, monitoring/fault tolerance, and performance tuning for large datasets, with experience deploying in cloud environments using containerization and CI/CD.”

SreeHarsha Kelam

Screened

Senior DevOps / Site Reliability Engineer specializing in cloud infrastructure

Atlanta, GA5y exp

“GCP-focused database/platform engineer with hands-on production experience operating Cloud SQL at scale, especially around performance tuning, reliability, and day-2 operations. Has supported migration from a single-instance database setup to a more scalable GCP architecture and built Terraform/Python automation for provisioning and recovery workflows.”

“Analytics candidate currently at Facteus with hands-on experience turning messy transactional data into trusted reporting layers in Snowflake and Power BI. They combine SQL and Python automation with strong validation, performance tuning, and stakeholder-facing metric design, including cohort-based retention and segmentation work that improved trust and adoption of analytics.”

“Candidate has hands-on project experience in healthcare analytics, using SQL, Python, and Power BI to analyze CMS hospital readmissions and HRRP penalty risk in Florida. Their work centers on turning messy CMS flat files into reporting-ready datasets, benchmarking hospitals against national references, and surfacing financial risk through dashboards.”

Adhiraj Chadha

Screened

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

Amherst, MA3y exp

“Builder with a mix of backend engineering, product instinct, and startup execution: they shipped a legal BI platform from scratch that handled 1,000+ cases, cut reporting time 80%, and saved $30K annually. They also move quickly in ambiguous environments, from launching a roommate app across iOS/Android after user discovery to building a RAG system with a 50+ case evaluation suite and a cloud dev environment in under 48 hours.”

Chinmay Warang

Screened

Senior Audio Software Engineer specializing in real-time audio ML systems

Somerville, MA5y exp

“Startup backend engineer with unusually deep end-to-end ownership of real-time audio/ML systems. At Modulate, they rebuilt the core Audio Intelligence API used by enterprise customers like Activision, cutting latency 70% and eliminating session loss, and also independently created a data labeling platform that powered the company’s model training during a major product pivot.”

“Backend engineer who built an AI-powered grant matchmaking platform for researchers and professors, combining semantic matching, embeddings, and Semantic Scholar enrichment with rule-based eligibility filters. Stands out for pragmatic AI engineering: they focused on reliability through confidence scoring, logging, manual validation, and production-minded backend design.”

“AI/full-stack product engineer currently owning Fleck Intelligent Survey Chatbot at E15, a production RAG analytics assistant embedded in Compass Group dashboards for 300+ field operators. Stands out for combining LLM orchestration, analytics engineering, and strong systems thinking—cutting hallucinated numeric answers from 14% to 2%, reducing backlog 62%, and previously delivering a low-level protocol redesign at Amadeus that cut P99 latency by 56%.”

“Full-stack engineer with startup experience building real-time collaboration and meeting platforms for enterprise customers. Has worked across product ownership, React/TypeScript frontends, Go and Node.js backend services, PostgreSQL data modeling, and production performance optimization in B2B SaaS environments.”

“Full-stack Python engineer who has owned internal automation products from requirements through production, including a financial reporting platform that improved deployment time by 45% and raised reporting efficiency to 98%. Also built an AI-powered movie recommendation engine using collaborative and content-based filtering, with hands-on experience across frontend, backend, data pipelines, and ML evaluation.”

“Full-stack/backend-heavy engineer with experience across real-time product systems and high-scale financial analytics, citing work on Flashcode, Netflix, and Bank of America via TCS. Particularly strong in Kafka-based event-driven architecture, streaming pipelines, and production performance tuning, with concrete wins including a 15% latency reduction and scaling reliability from 30k to 50k+ concurrent events.”

“Backend engineer who built a real-time, event-driven alerting platform (Java/Spring Boot, Kafka, MongoDB) processing millions of events per day on AWS (Docker/Kubernetes), including hands-on performance debugging of Kafka consumer lag at peak. Also shipped an end-to-end LLM-based alert summarization feature and designed a multi-step incident triage agent workflow with retries and human-in-the-loop escalation.”

“Backend/microservices engineer (Java/Spring Boot, Kafka, Angular microfrontends) with Teradata experience building distributed analytics/query routing platforms and delivering 20–30% latency reductions through event-driven redesign and reliability hardening. Also built and shipped an end-to-end multimodal medical imaging AI feature (LLaVA/Mistral 7B + LoRA) with production guardrails like confidence-based human review, drift monitoring, and audit logs.”

“Backend/real-time systems engineer transitioning into robotics software: building ROS 2 fundamentals (pub/sub, custom messages, launch files) and experimenting with Nav2 + SLAM in Gazebo/RViz. Demonstrated practical debugging by tuning costmaps/planners and analyzing topic latency to stabilize simulated navigation, and has experience integrating telemetry pipelines and REST-based external interfaces.”

“Full-stack engineer and ML assistant in UC Irvine’s CS department who deployed a lab project showcase platform and integrated on-demand execution of computational projects using Docker for isolation. Also built and optimized Linux cloud/cluster test automation for research, diagnosing RAM and network sync bottlenecks, and later led development of a Python-based predictive analytics tool for musicians using probabilistic graphical models and flexible data pipelines.”

“Software engineer experienced in e-commerce systems, building customer-facing features and internal operations tools with TypeScript/React frontends and Spring Boot microservices. Demonstrated measurable performance wins (order-tracking API improved from ~2s to <700ms) and strong event-driven reliability practices with RabbitMQ (idempotency, DLQs, retry/backoff), including resolving a production queue backlog incident. Built an ops dashboard with real-time cross-service order tracing that became a daily tool for support/ops and reduced escalations to engineering.”

“Backend/AI engineer who built an AI icon-generation SaaS backend (Java/Spring Boot, MongoDB) on AWS, including async job processing with idempotency and S3-based result storage to handle traffic spikes. Also shipped applied AI in finance—an end-to-end fraud detection pipeline with risk scoring—and designed a banking support AI agent with strict guardrails, audit logs, and human-in-the-loop escalation.”

“Backend/platform engineer who owned a Python-based smart finance assistant backend, building async FastAPI microservices with PostgreSQL/Redis and deploying to AWS EKS via Docker/Helm and CI/CD (GitHub Actions, Jenkins). Strong in production reliability and migrations—implemented observability (Prometheus/Grafana), security (JWT RBAC), and executed a low-downtime monolith-to-microservices migration plus Kafka-based event streaming with ordering/retry/idempotency patterns.”

“Full-stack engineer with recent Mutual of Omaha experience building a cloud-native microservices application in Java/Spring Boot with a React/Angular frontend, integrating multiple AWS services (Lambda, S3, DynamoDB, SQS). Has hands-on experience operationalizing AI features via OpenAI/AWS Bedrock and improving reliability/performance through caching, async processing, and CI/CD pipeline optimization.”

“AI/LLM engineer with production experience in legal tech: built a GPT-4 + LangChain RAG summarization system at Govpanel that reduced legal case-file review time by 50%+. Previously at LexisNexis, orchestrated end-to-end Airflow data/AI pipelines processing 5M+ legal documents daily, improving ETL runtime by 35% with robust validation, monitoring, and SLAs.”

“Built and shipped production generative AI/RAG assistants in regulated financial contexts (S&P Global), automating compliance-oriented Q&A over earnings reports/filings with grounded answers and citations. Experienced across the full stack—AWS-based ingestion (PySpark/Glue), vector retrieval + LangChain agents, GPT-4/Claude model selection, and production reliability (monitoring, caching, retries) plus rigorous evaluation and regression testing.”

“Backend-leaning full-stack engineer with logistics domain experience (DHL) who shipped a real-time shipment status update system using Spring Boot + Kafka and a performance-tuned PostgreSQL tracking schema. Also has AWS production operations experience (ECS/Kubernetes, Jenkins CI/CD, Terraform/Ansible) and has handled peak-load incidents end-to-end by tracing Kafka lag to database bottlenecks and resolving via query/index optimization plus scaling.”

“AI/ML-focused backend engineer who shipped two production systems: PersonaPal (agentic LLM chatbot with RAG, FAISS-based retrieval, and Redis semantic caching) and CervixScan (clinical diagnostics platform with PostgreSQL data modeling and human-in-the-loop safety for low-confidence predictions). Demonstrates strong performance/reliability work (indexed vector search, caching, query optimization to ~200ms) and end-to-end ownership from orchestration design through deployment.”

“Full-stack engineer (4+ years) with Citigroup experience building a modular banking dashboard using React/TypeScript/Redux and a Java Spring Boot microservices backend (12+ services) integrated with Kafka. Strong in reliability/observability and cloud operations on AWS (EC2/S3/Lambda, CloudWatch, Prometheus, ELK, IaC with Terraform/CloudFormation), with quantified improvements in latency, development speed, and data pipeline correctness.”