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Vetted Data Warehousing Professionals
Pre-screened and vetted.
Mid-level Data Scientist / ML Engineer specializing in NLP, recommender systems, and insurance analytics
Senior Solution Architect and Engineering Manager specializing in government, FinTech, and cloud platforms
Mid-level Data Engineer specializing in AWS ETL and data warehousing
Mid-Level Backend Software Engineer specializing in FinTech and data pipelines
Executive Commerce & Digital Technology Leader specializing in enterprise eCommerce platforms
Senior Software Engineer specializing in backend, platform, and marketplace systems
Executive engineering leader specializing in FinTech and AI platforms
Mid-level Machine Learning Engineer specializing in NLP, federated learning, and fraud detection
Executive AI & Technology Leader specializing in enterprise data, GenAI, and digital transformation
Principal Data Scientist specializing in Generative AI and MLOps
Technology Executive specializing in AI-native engineering and cybersecurity governance
Mid-level AI/ML Data Engineer specializing in data pipelines, MLOps, and LLM/RAG systems
Mid-level Full-Stack Python Developer specializing in cloud-native FinTech and GenAI
Mid-level Data Engineer specializing in cloud lakehouse platforms (Azure/AWS/Snowflake)
Executive Chief Data & Analytics Officer specializing in data modernization and AI governance
Mid-level Business Analyst specializing in data analytics and enterprise reporting
Nehal Mahankali
Mid-level Full-Stack Python Developer specializing in cloud-native banking applications
“Backend engineer who built a low-latency real-time transaction API in Python/Flask, with strong depth in PostgreSQL/SQLAlchemy performance tuning (time-based partitioning, indexing, connection pooling). Has production experience integrating ML scoring and OpenAI-style APIs with safety/latency controls, and designing multi-tenant isolation strategies including per-tenant pooling/caching and premium-tenant isolation.”
Sanketh Reddy
Senior Data Engineer specializing in cloud data platforms and large-scale ETL
“Data engineer focused on large-scale ETL/ELT pipelines across cloud stacks (GCP and AWS), including Spark-based transformations and orchestration with Airflow. Has experience loading up to ~2TB per BigQuery target table and designing atomic loads to multiple downstream systems (Elasticsearch + Kafka), with Kubernetes deployment and Jenkins CI/CD.”
Vikas Ravula
Senior Data Engineer specializing in cloud data platforms and real-time streaming for financial services
“Data engineer with experience at Bloomberg, UBS, and Bank of America building high-volume financial data platforms and services. Owned an end-to-end pipeline processing ~150–200M records/day (Kafka/Cassandra/S3 → Spark/PySpark → Snowflake) with strong data quality controls and Airflow reliability practices, reporting ~99% reliability and major performance gains. Also built large-scale external API ingestion with compliance-minded rate limiting, schema versioning, and quarantine/validation layers.”
Abhay Murjani
Director-level Data Science Manager specializing in ML forecasting, experimentation, and MLOps
“Data/ML engineer with experience at American Express and Amazon, owning an end-to-end rewards redemption/liability ML pipeline (~200GB) with rigorous regulatory/audit validation and quarterly executive reporting. Also built web-scraped product datasets with anti-bot protections at a startup and helped modernize an authn/authz service using AWS, plus led early-stage migration work from an internal warehouse to GCP with CI/CD and cloud observability.”