Vetted Schema Validation Professionals

“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.”

“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.”

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).”

“Analytics-focused candidate with experience owning end-to-end data projects across AI transcription, retail forecasting, and transportation revenue analytics. They combine strong SQL/Python pipeline skills with dashboarding and stakeholder alignment, citing measurable impact including 60% lower ETL latency, 18% better forecast accuracy, and 25% operational efficiency gains.”

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.”

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.”

“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.”

“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.”

Chuangyu Xu

Screened

Entry-Level Software Engineer specializing in Java backend and distributed systems

New York, NY

“Built and shipped a production AI mock-interview platform where an LLM “interviewer” generates role-specific questions, runs multi-turn follow-ups, and outputs structured scoring/feedback using RAG. Demonstrates strong production-readiness practices (Prometheus/Grafana monitoring, retries/timeouts, fallback models/templates, schema validation, replay-based debugging) and achieved 99%+ availability with ~40% higher session completion. Also has experience integrating agents with messy SAP/ERP-style data sources using a data middleware layer, cleaning/validation, and idempotent write safeguards.”

“QA automation engineer with Silicon Valley Bank experience owning end-to-end test automation for customer onboarding and payments. Built a hybrid framework (Playwright UI, REST Assured API, Python + SQL backend validation) integrated into Azure DevOps CI/CD with PR gating and nightly regressions, catching high-risk issues like silent API contract breaks and missing payment ledger entries before release.”