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Vetted Data Modeling Professionals
Pre-screened and vetted.
Mid-level Solutions Engineer specializing in ads platforms and ML-driven marketing systems
Akshat Shah
Entry-level Software Engineer specializing in full-stack and AI systems
“Frontend-leaning full-stack engineer who described owning an artist search and detail experience across UI, backend integrations, and data modeling. They show practical strength in scalable React architecture, TypeScript safety, and performance tuning, with a product-minded approach to shipping 0→1 features quickly and iterating after launch.”
Rashi Agrawal
Mid-Level Full-Stack Software Engineer specializing in distributed systems and cloud-native microservices
“Backend engineer (4 years) who built an end-to-end Python backend for a patent-pending in-car massager/heater system, including GraphQL data modeling and Bluetooth integration with an ESP32 microcontroller (reverse engineered a niche protocol). Also has strong platform experience: on-prem Kubernetes/CI-CD (Jenkins/GitLab, exploring ArgoCD GitOps), Terraform-based infra workflows, a RabbitMQ messaging library used across microservices, and an on-prem migration of ~30 critical applications with rollback/parallel-run strategy.”
Rom Manzano
Executive technical founder and full-stack engineer specializing in AI, SaaS, and FinTech
“Engineer coming out of a venture studio as it winds down, now seeking another zero-to-one environment with strong studio support and go-to-market playbooks. They show a thoughtful founder mindset centered on rapid shipping, design-partner validation, lean execution, and testing whether users will actually pay for a workflow-specific solution.”
Amrita Pritam
Senior Backend Engineer specializing in distributed microservices and event-driven systems
“Backend engineer with production experience building a high-scale notification pipeline (~20M/day) using Java/Dropwizard with Kafka and Azure Queue, including DLQ/poison-message handling and the outbox pattern for reliability. Also led a batch-based migration of Yammer Messaging user data from PostgreSQL to Azure Cosmos DB for global multi-region scale, addressing throttling and network failures via retries, escalation policies, and dynamic throughput tuning.”
Mid-level AI/ML Engineer specializing in NLP/LLMs and production ML systems
Mid-level Data Engineer specializing in cloud data pipelines and lakehouse/warehouse platforms
Mid-Level Full-Stack Software Engineer specializing in test automation platforms
Director-level Program Management leader specializing in private equity portfolio operations
Mid-level Business Analyst specializing in data analytics and financial systems
Senior Software Engineer specializing in AI/LLM and distributed cloud systems
Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines
Mid-level Data Engineer specializing in cloud-native big data pipelines and analytics
Senior Backend Engineer specializing in Healthcare & Cloud Platforms
Senior Software Engineer specializing in data lineage and cloud data platforms
Senior Data Engineer specializing in cloud data platforms and large-scale ETL
Mid-level Data Engineer specializing in big data platforms and analytics infrastructure
Rhutwij Tulankar
Engineering Manager and ML/Data Architect specializing in scalable data platforms and personalization
“Hands-on engineering manager at a marketing company leading a highly senior, distributed team (10 direct reports) while personally coding ~60–70% and owning end-to-end architecture across three interconnected products. Built agentic CRM automation and a reinforcement-learning-driven distribution layer for channel spend/bidding, with a strong focus on scalable design and observability (Prometheus/APM/logging) enabling frequent releases and few production incidents.”
Venu Dave
Junior Software Development Engineer specializing in backend data platforms and LLM applications
“Amazon internship experience building and shipping an end-to-end NL-to-SQL system: ingested/normalized metadata across 60+ internal tables, added rigorous multi-layer validation for LLM-generated SQL, and served it via a FastAPI backend for engineers—driving 90%+ faster dataset discovery and ~70% lower effort to access data. Also built an early-stage RAG-based healthcare assistant, iterating on chunking, embeddings, and retrieval to improve answer quality post-launch.”