Vetted Data Modeling Professionals

“Healthcare data engineer with hands-on ownership of claims/member data pipelines on a cloud analytics platform, spanning batch and streaming ingestion (Airflow/Kafka/Spark/Databricks) through serving for reporting. Emphasizes reliability and data quality via embedded validation, schema-drift detection, deduplication, and operational monitoring/incident response, plus pragmatic CI/CD and observability setup in early-stage/ambiguous projects.”

Venkata Surya Yashwanth Varma Vadlamudi

Screened

Junior Software Engineer specializing in distributed systems and full-stack web development

Ithaca, NY2y exp

“Software engineer at Cimpress owning end-to-end transactional pages for Pens.com (e-commerce). Built and integrated new discount experiences in a React/TypeScript + Node.js stack, focusing on modular component architecture to reduce tight coupling and avoid breaking existing functionality; prioritizes roadmap work using performance and conversion metrics.”

Akashreddy Madduri

Screened

Senior Backend Engineer specializing in real-time data platforms for FinTech and Healthcare

Plano, Texas6y exp

“Backend/data engineer with experience at JPMorgan building near real-time payment risk and fraud scoring pipelines using Python, Spark Structured Streaming, and Delta Lake, emphasizing auditability, security, and data correctness (dedupe/late events) to reduce false positives. Also led a legacy-to-cloud migration of claims/eligibility data at Cogna with parallel runs, phased rollout, and healthcare-specific validation (ICD-CPT mapping).”

Sarthak Vinayaka

Screened

Mid-Level Full-Stack Software Engineer specializing in enterprise AI, data pipelines, and scalable APIs

Redwood City, CA3y exp

“Forward-deployed engineer/tech lead who built an end-to-end demand planning and forecasting application for a major US steel manufacturer, integrating Snowflake data into the C3 platform with batch/MapReduce workflows, monitoring, and a React/TypeScript UI. Also productionized an enterprise LLM integration with structured outputs and authorization guardrails, reporting +30% stakeholder engagement and broad adoption across customer deployments.”

Shram Kadia

Screened

Mid-level Software Engineer specializing in backend systems, cloud-native apps, and AI platforms

Santa Clara, CA4y exp

“Backend/full-stack engineer who has owned production systems end-to-end, including a Dockerized Node.js/TypeScript probabilistic fault-tree analysis service for nuclear safety research deployed on AWS. Also built and operated a FastAPI-based RAG pipeline over 200+ PDFs using FAISS, focusing on low-latency, idempotent workflows and strong observability; experienced with API design and Playwright E2E automation across React/Angular projects.”

Sushma Mangalampati

Screened

Mid-level Data Engineer specializing in lakehouse ETL and analytics engineering

Boston, MA6y exp

“Data engineer with strong end-to-end ownership of production lakehouse pipelines (Snowflake + Databricks + Airflow + dbt + Great Expectations), handling 8M+ records/month and 500K+ daily CDC updates. Delivered measurable reliability and efficiency gains (41% cost reduction, freshness improved from 4h to 30m, 35% fewer downstream incidents) and has experience building a lakehouse platform from scratch across 12 source systems.”

Barbara Christina Cruze

Screened

Senior Business Analytics Consultant specializing in BI, data engineering, and predictive analytics

Dallas, TX8y exp

“Healthcare analytics candidate with hands-on experience turning messy claims, enrollment, and reference data into trusted SQL reporting layers and reproducible Python workflows. They emphasize metric standardization, stakeholder alignment, and operational impact, including ~40% reduction in manual reporting effort and improved forecasting/resource prioritization through high-risk patient segmentation.”

“Analytics professional with experience across retail and healthcare, including Kroger and CVS Health. They have built SQL and Python workflows to clean and operationalize messy data, and have owned patient adherence/retention analytics projects that informed targeted interventions and improved refill and retention reporting.”

“Analytics engineer/data analyst with Bank of America experience turning fragmented financial data across SQL Server, PostgreSQL, Kafka, and flat files into trusted Snowflake/dbt reporting models. Stands out for unifying disputed business definitions like churn and payment success rate, automating manual analysis in Python, and pairing strong data quality rigor with stakeholder adoption through self-service dashboards.”

“Candidate has not formally held an SDR title but has already been doing structured outbound through recruiting and networking with measurable results. They stand out for turning targeted LinkedIn and email outreach into consistent weekly conversations and interviews, especially in equity research, while showing a thoughtful approach to personalization, cadence design, and early pipeline building.”

“Currently at Berryble AI, this candidate is building an LLM-based real-time interview analysis engine using FastAPI, WebSockets, fine-tuned models, and GCP/Cloud Run. They stand out for using AI and agent workflows pragmatically to accelerate development while keeping human ownership over architecture, security, reliability, and maintainability, and they are also pursuing a master's in applied machine learning.”

“ML/AI engineer with strong production depth across classical ML, MLOps, LLM/RAG, and scalable Python data platforms, with experience at Cisco and Accenture. Stands out for tying technical decisions to measurable business outcomes, including $1.2M annual savings, 40% faster support resolution, and broad internal adoption of shared engineering frameworks.”

“Built production-scale dashboards and real-time data systems across fintech and autonomous driving, with hands-on ownership from React frontend architecture through Python/Kafka/Elasticsearch backend pipelines. At Zoox, led development of an automated safety signal attribution platform that replaced manual engineering calculations and surfaced trends through dashboards.”

“Hands-on engineering leader who has scaled teams quickly (hired 20 engineers in 4 months) and led major architecture shifts including monolith-to-microservices and serverless, async AI-driven medical data ingestion/search. Also drove a versioned-inventory redesign with auditability and rollback that reduced operational errors by 22%, and demonstrates strong incident response with clear stakeholder communication.”

“Full-stack product builder with strong GTM and applied AI experience, including end-to-end ownership of a production lead intelligence platform that combined React/TypeScript, Python services, external data enrichment, and LLM orchestration. Notably reduced SDR research time from 15-20 minutes to under 2 minutes per account and also drove an 8% revenue increase at Finding Pi by building a customer segmentation framework from analysis of 45k+ users.”

“Frontend-focused engineer with experience spanning healthcare, enterprise analytics, and real-time trading products. They have owned React/TypeScript dashboard surfaces end-to-end, including a hospital patient dashboard that cut latency by 50%, and have also shaped backend WebSocket contracts to make real-time systems scale.”

Vasudev Konde

Screened

Mid-level Full-Stack Java Developer specializing in APIs and cloud microservices

Phoenix, AZ5y exp

“AI/LLM engineer who has shipped a production document-intelligence agent that automated internal support workflows using RAG, tool calling, and robust fallback controls. Stands out for combining hands-on architecture with measurable business impact: 85% faster query resolution, 35% lower LLM cost, 40% fewer LLM calls, and enough automation to avoid adding 2-3 support engineers.”

Becky Dubrow

Screened

Director-level Product Leader specializing in SaaS and cybersecurity platforms

Remote, USA21y exp

“Security product leader with deep experience spanning Bishop Fox, Malwarebytes, and startup environments, combining platform architecture, AI-enabled security workflows, UX judgment, and org leadership. Notably re-architected offensive security platforms, introduced human-in-the-loop AI systems, and scaled a consumer business from $17M to $120M+ ARR while growing and mentoring global product teams.”

“Senior product leader with a track record of rebuilding complex enterprise products in legal tech, martech, and financial data. Notably transformed Recommind's eDiscovery UX ahead of its $163MM acquisition and now builds high-scale LLM-powered SEC filing analysis at FeeLogic, combining strong AI product judgment with a human-centered philosophy for high-stakes workflows.”

“Full-stack engineer focused on high-throughput document/financial data platforms, building Angular/React front ends and Spring Boot microservices with Python/Flask services for heavy processing. Experienced in designing non-blocking, asynchronous workflows (Celery/RabbitMQ) and deploying containerized systems to AWS ECS with auto-scaling and CloudWatch monitoring.”

Harshal Sawant

Screened

Senior AI Engineer specializing in LLMs, RAG, and MLOps on multi-cloud

8y exp

“Built and productionized a secure internal RAG-based AI assistant (LangChain/FastAPI/FAISS on GCP), tackling real-world issues like latency, retrieval speed, and hallucinations—delivering 25% faster retrieval and 99.9% uptime. Also implemented scalable, reliable ML retraining orchestration with AWS Step Functions/SageMaker/Lambda and partners closely with compliance analysts to iteratively refine prompts and outputs to meet governance standards.”