Vetted User Acceptance Testing (UAT) Professionals

“Dynamics 365 Project Operations/Field Service implementer focused on operational execution—built foundational task tracking and expedited field-service scheduling with improved visibility, alerts, and billing/sales record traceability. Uses interviews plus pilot/testing to refine UI and business processes for adoption, and applies A/B testing techniques to both marketing emails and D365 form experiences while partnering with the D365 product team to address bugs and usability.”

Bhanu Chander

Screened

Senior Data Engineer specializing in cloud data platforms and real-time pipelines

New York, NY6y exp

“Data engineer focused on reliability and observability, building end-to-end pipelines processing millions of records/day from sources like S3 and Kafka. Has hands-on experience with Airflow-based data quality automation, PySpark/Databricks transformations, and shipping versioned Python REST APIs deployed via Docker/Kubernetes with CI/CD (Jenkins) and monitoring (CloudWatch/Azure Logs).”

“Enterprise implementation leader with 10+ years delivering multi-million-dollar B2B/SaaS rollouts across procurement, expense management, legal tech, and fraud/identity platforms. At Amazon Business, managed 12+ concurrent enterprise implementations and owned the full lifecycle from strategy and change management through go-live, with strong executive stakeholder management and governance discipline.”

Anson T P

Screened

Staff Software Engineer specializing in Salesforce, mobile, and IoT platforms

Bengaluru, India12y exp

“Frontend-leaning product engineer with strong end-to-end ownership across mobile observability, real-time systems, and scalable React/Next.js architecture. Built a reusable iOS logging framework integrated with Splunk, designed IoT operator dashboards, and shaped a JSON-driven website rendering platform by aligning product, backend, and frontend models.”

“Java full-stack developer who has owned data-intensive, customer-facing and internal web products end-to-end (React/Angular + Spring Boot), including CI/CD and production support. Demonstrates deep microservices experience with RabbitMQ/event-driven architecture, idempotency, DLQs, and compensating logic to maintain reliability and data consistency at scale, plus a track record of replacing spreadsheet-based ops reporting with an adopted real-time internal tool.”

“Data/ML engineer with experience across pharma (Dr. Reddy Laboratories) and financial services (Cincinnati Financial, Capital One), building production NLP and entity-resolution systems that connect messy unstructured text with enterprise SQL data. Delivered semantic search with BERT + vector DB and domain fine-tuning (reported ~35% relevance lift), and builds robust pipelines using Airflow/dbt/Spark with strong validation, monitoring, and stakeholder-aligned rollout practices.”

“Enterprise SaaS implementation specialist (Sprinklr) who owns complex rollouts end-to-end—configuration, data migration, UAT, global enablement—and drove a 10/10 Customer Happiness Index plus renewal/expansion through strong adoption and analytics automation. Also has product experience from a TikTok PM internship leading an accessibility initiative (Camera AI for screen reader creators) coordinating engineering, design, legal, and QA with WCAG/ADA/EAA compliance considerations.”

“Analytics-focused candidate with hands-on experience building SQL reporting tables from messy transactional and master data, plus Python workflows that automate monthly analysis and data checks. They appear strongest in KPI/reporting ownership, metric standardization, and stakeholder alignment, with examples of improving reporting consistency, surfacing issues earlier, and reducing manual reconciliation effort.”

Margil Gandhi

Screened

Mid-level Product Leader specializing in AI, FinTech, and Travel Tech

Dallas, TX5y exp

“Product leader and startup co-founder with ~6 years of end-to-end ownership, spanning a travel SaaS business and AI workflow products at Goldman Sachs. Particularly compelling for AI/knowledge products: built a RAG-based Copilot used by 2,000+ agents with ~95% answer accuracy in a regulated environment, and also created a side-project knowledge engine indexing 270 podcast episodes with semantic search and citations.”