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Vetted Databricks Professionals
Pre-screened and vetted.
Mid-level Data Engineer specializing in AI, analytics, and cloud data platforms
Junior Software Engineer specializing in GenAI and backend systems
Mid-level AI & Data Engineer specializing in RAG and analytics platforms
Mid-level AI/ML Engineer specializing in LLMs, RAG, and agentic AI systems
Mid-level Data Scientist / Software Engineer specializing in AI automation and cloud microservices
Senior QA Engineer specializing in automation, API testing, and data quality validation
Junior Data Scientist specializing in cybersecurity and AI/ML
Mid-Level Machine Learning Engineer specializing in LLMs and RAG systems
Intern Data Scientist / ML Engineer specializing in predictive modeling and data pipelines
Mid-level Data Analyst specializing in marketing analytics and machine learning
Senior Full-Stack Product Engineer specializing in AI, Cloud, and regulated domains
Mid-level AI/ML Engineer specializing in GenAI, RAG, and multi-agent LLM systems
Senior Full-Stack Engineer specializing in Python, cloud-native microservices, and React
Mid-level SQL Developer specializing in MySQL, ETL, and cloud data pipelines
Snigdha Reddy Podduturi
Junior Data & AI Engineer specializing in cloud AI and analytics
“Built production AI backend systems in healthcare and e-commerce, including a healthcare agent that automated clinical workflows like medication refills, immunizations, and scheduling using FHIR APIs and cloud-native infrastructure. Strong in end-to-end backend ownership, LLM orchestration, and adding guardrails/validation for high-stakes and customer-facing AI workflows.”
Hetal Pambhar
Mid-level Data Engineer and Analytics Analyst specializing in business growth and marketing insights
“Analytics professional with operations-grounded experience at WWEX Group who built a Snowflake/dbt fleet-efficiency data model combining telematics, ERP, and driver logs into near real-time executive reporting. They pair strong SQL/Python workflow automation with practical stakeholder enablement, and cite measurable impact including cutting reporting time from 72 hours to 15 minutes and helping drive $450K in quarterly fuel savings.”
Lakshmi Swathi Sreedhar
Mid-level AI Engineer specializing in Generative AI and LLM systems
“Built and deployed a production-grade, multi-agent Text-to-SQL assistant that lets non-technical stakeholders query large enterprise databases in natural language. Uses Pinecone-based schema retrieval + LLM reasoning (Gemini/Claude/GPT) with a dedicated validation agent (schema/syntax checks and safe dry runs) to reduce hallucinations and improve reliability, while optimizing latency and cost via async execution and embedding caching.”
VIJAY SAGI
Mid-level Data Engineer specializing in cloud-native batch and streaming pipelines
“Data/ML platform engineer with ~6 years in financial services and enterprise data platforms, building regulated fraud/credit-risk pipelines on AWS (Airflow, EMR/Spark, MLflow) and an Azure lakehouse ingesting 50+ sources and serving ~100M records/day. Also led an early-stage deployment of a RAG-based internal AI search tool using AWS Bedrock and LangChain with automated evaluation to validate LLM accuracy.”
Karan Savaliya
Junior Backend Engineer specializing in data platforms and cloud APIs
“Backend lead at a stealth startup and builder of MailIQ/MailBox—an automated Gmail inbox digest + cleanup system. Designed secure multi-account email ingestion and cost-efficient LLM-based summarization, and implemented robust unsubscribe automation using Playwright + OpenAI webpage analysis (including captcha-handling) with strong safety guardrails, incremental rollouts, and rollback strategies.”
Vengalarao Pachava
Junior AI Data Engineer specializing in Azure Databricks lakehouse and GenAI RAG systems
“Backend/applied AI engineer from Cloud Rack Systems who built production GenAI/RAG and data platforms on Azure/Databricks at enterprise scale (2.5M records/day). Known for making LLM systems behave like deterministic services via strict retrieval contracts, citation-based validation, and strong observability—shipping a knowledge assistant used daily by 50+ users while driving hallucinations near zero and materially improving latency and cost.”
Shrey Shah
Junior Data Analyst specializing in BI, SQL, and business analytics
“Analytics professional with experience across Dreamline AI, Ultron Technologies, and Infolabz, building SQL/Python data pipelines and BI dashboards for incentive, FMCG, and retail use cases. Stands out for turning messy multi-source data into trusted reporting, automating recurring analytics, and tying dashboard adoption to measurable business outcomes like 50% faster reporting and 30% ROI improvement.”