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Vetted Data & Analytics Professionals
Pre-screened and vetted.
Popular Titles
Mid-level Data Engineer specializing in lakehouse architectures and cloud ELT
Mid-level Data Scientist / ML Engineer specializing in NLP, GenAI, and cloud ML deployment
Junior Customer Success Business Analyst specializing in B2B SaaS analytics and retention
Mid-level Data Engineer specializing in cloud data platforms for Healthcare and Financial Services
Mid-level Data Engineer specializing in cloud lakehouse and real-time streaming
Mid-level Data Analytics Engineer specializing in ETL pipelines and BI dashboards
Senior Data Engineer specializing in multi-cloud lakehouse architectures and privacy/AI governance
Junior Data Engineer specializing in cloud data platforms and MLOps
Mid-level Supply Chain & Business Analyst specializing in SQL/Python analytics
Mid-level Business Analyst and Product Analyst specializing in data-driven operations
Mid-level Business Analyst specializing in sales analytics and revenue strategy
Mid-level Data Analyst specializing in healthcare and financial analytics
Senior Power BI Developer specializing in healthcare and financial analytics
Mid-level Data Analyst specializing in business intelligence and predictive analytics
Mid-level Data Analyst specializing in financial, operational, and regulatory reporting
Senior Data Scientist and AI Engineer specializing in NLP, LLMs, and MLOps
Mid-level Data Engineer specializing in AWS data lakes for healthcare and financial services
Senior Data Scientist specializing in NLP, MLOps, and cloud ML platforms
Ruudra Patel
Junior Data Scientist specializing in ML, LLMs, and RAG applications
“University hackathon finalist (2nd place) who built CareerSpark, a production-style multi-agent career guidance app in 24 hours using a hierarchical debate architecture with a moderator/judge agent. Has startup internship experience at LiveSpheres AI using LangChain for multi-LLM orchestration, and demonstrates a structured approach to testing/evaluation (golden sets, integration sims, latency/accuracy KPIs) plus strong non-technical stakeholder communication.”
Vardhan Are
Mid-level Data Analyst specializing in AWS-based ETL, churn analytics, and BI dashboards
“Data/ML practitioner with experience at Airtel and Lincoln Financial delivering measurable business outcomes: improved retention 15% via NLP sentiment analysis and cut response time ~25% using sentence-BERT + FAISS semantic linking. Strong in data quality/identity resolution (SQL + fuzzy matching) and in building production-grade Python workflows orchestrated with Airflow/AWS Glue, including validation and dashboard integration in Power BI.”
Sri Niyati Kompella
Senior Data Engineer specializing in cloud data platforms and ML pipelines
“Data engineer focused on AWS-based enterprise data platforms, owning end-to-end pipelines from multi-source batch/stream ingestion (Glue/Kinesis/StreamSets/Airflow) through PySpark transformations into curated datasets for Redshift/Snowflake. Emphasizes production reliability with strong monitoring/observability and data quality gates, and reports ~30% performance improvement plus improved SLAs and latency after optimization.”
Parvinder Singh
Mid-level Data Engineer specializing in AWS lakehouse platforms and scalable ETL/ELT
“Data engineer focused on reliable, production-grade pipelines and data services: has owned end-to-end ingestion-to-serving workflows processing millions of records/day, using Airflow, Python/SQL, and PySpark. Demonstrates strong operational rigor (monitoring, retries, idempotency, backfills) and measurable outcomes (98% stability, ~30% faster processing), plus experience exposing curated warehouse data via versioned REST APIs.”
Varshitha K
Mid-level Data Engineer specializing in cloud data platforms and lakehouse architectures
“Data engineer in a banking context who has owned end-to-end Azure lakehouse pipelines ingesting financial/vendor data from APIs, Azure SQL, and flat files into Databricks/Delta (bronze-silver-gold). Emphasizes production reliability via schema-drift validation, data quality controls, monitoring/alerting, retries/checkpointing, and Spark/Delta performance tuning, with outputs served to BI/reporting teams (e.g., Tableau).”
Chandan Chalumuri
Mid-level Data Scientist specializing in ML, NLP, and Generative AI
“Data engineering / ML practitioner with experience at MetLife building transformer-based sentiment analysis over large unstructured datasets and productionizing pipelines with Airflow/PySpark/Hadoop (reported 52% efficiency gain). Also implemented embedding-based semantic search using Pinecone/Weaviate to improve retrieval relevance and enable RAG for customer support and document matching use cases.”