.png){kind=logo}
Vetted Azure SQL Database Professionals
Pre-screened and vetted.
Mid-Level Full-Stack Software Developer specializing in Healthcare IT and FinTech
Mid-level Data Engineer specializing in cloud ETL, streaming, and data warehousing
Executive technology leader specializing in supply chain, logistics, and AI platforms
Mid-level Full-Stack .NET Developer specializing in Angular, Azure, and AI integrations
Staff AI/ML Engineer specializing in backend platforms and LLM systems
Mid-level Full-Stack Developer specializing in cloud-native web apps and FinTech
Mid-level Software Engineer specializing in FinTech and scalable backend systems
Senior .NET Full-Stack Developer specializing in cloud-native microservices
Executive Engineering Leader specializing in Product, Mobile, and SaaS platforms
“Built and operated end-to-end legal-document data pipelines fed by hundreds of scraper sources, emphasizing data quality validation, reliability (CloudWatch monitoring/alerting, retries, backfills), and serving enriched legal data via serverless AWS APIs (Lambda/API Gateway). Experienced in keeping API contracts stable with additive versioning practices and shipping MVPs quickly with CI/CD and observability in place.”
Mid-level Cloud Data Engineer specializing in multi-cloud data platforms and analytics
Senior .NET Full-Stack Engineer specializing in enterprise web apps and cloud platforms
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices
Senior Performance Marketing & Marketing Operations Manager specializing in automation and analytics
Mid-level Full-Stack Developer specializing in modern web apps and cloud DevOps
Mid-level Full-Stack Software Developer specializing in cloud microservices and healthcare interoperability
Priyanka Ramesh
Junior Full-Stack Software Engineer specializing in Java/Spring Boot and React
“Backend engineer (IpserLab) who owned Python services for a production quiz/analytics platform, focusing on reliability and low-latency behavior under peak load. Hands-on with Kubernetes + Docker deployments and GitHub Actions CI/CD in a GitOps-style workflow, including solving configuration drift and enabling fast rollbacks. Also implemented Kafka-based event streaming with idempotent consumers and strong observability (lag tracking, structured logging, alerting).”
Tanweer Ashif
Mid-level AI/ML Engineer and Data Scientist specializing in LLMs and MLOps
“Data science/AI intern at University at Buffalo Business Services who built and deployed production systems spanning classic ML and LLM assistants. Delivered real-time competitor intelligence for a Cornell-partnered, $1B beverage launch by scraping/cleaning 5,000+ SKUs and deploying models via API, then built a domain-aware LLM assistant to modernize Excel-based workflows with strong grounding, privacy controls, and sub-5s latency.”