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Vetted Data Quality Professionals
Pre-screened and vetted.
Executive AI/CTO leader specializing in agentic LLM platforms and enterprise architecture
Senior Data Engineer specializing in AWS cloud migration and big data pipelines
Mid-level Data Engineer specializing in cloud data platforms for financial services and healthcare
Executive data and engineering leader specializing in healthcare cloud and AI platforms
Mid-level Data Engineer specializing in cloud ETL and real-time analytics
Mid-level Backend/Distributed Systems Engineer specializing in cloud-native data pipelines
Senior Customer Success & Analytics professional specializing in BI and cross-functional strategy
Intern Data Analyst/Data Scientist specializing in product analytics and ML
Mid-level Data Engineer specializing in streaming, lakehouse platforms, and LLM-driven data workflows
Director-level Product Data Science leader specializing in experimentation and causal inference
Mid-level Data Scientist specializing in marketing analytics and scalable data platforms
Executive Technology Leader specializing in enterprise transformation and AI-driven product innovation
Mid-level Data Engineer specializing in streaming and cloud lakehouse platforms
Mid-level Data Engineer specializing in AWS, Spark, and streaming data pipelines
Staff Salesforce Engineer specializing in enterprise CRM and integrations
Senior AI/ML Engineer specializing in GenAI, LLMs, NLP, and MLOps
Rubeena Riyas
Senior AI Engineer specializing in LLM agents, RAG, and scalable data platforms
“ML/data engineer who owned an end-to-end production sales analytics pipeline at 15,000+ user scale, delivering ~50% compute reduction, ~80% faster reporting, and ~$1.2M impact. Also shipped a production RAG-based AI assistant over internal BigQuery/docs with evaluation metrics and safety guardrails, and built shared Python libraries to standardize reliability and accelerate engineering teams.”
JYOTHI N
Senior Data Scientist specializing in analytics, experimentation, and BI on AWS
“Data/ML practitioner focused on healthcare data quality and record linkage: analyzed 10M+ records, built anomaly detection and NLP-driven entity resolution, and automated AWS ETL/validation pipelines (Glue/Redshift/Lambda), cutting data errors by 40% and generating $500k in annual savings. Has hands-on experience with embeddings (Sentence Transformers/spaCy), FAISS vector search, and fine-tuning for domain-specific matching.”