.png){kind=logo}
Vetted PySpark Professionals
Pre-screened and vetted.
Madhav Vaddepalli
Senior Data Engineer specializing in cloud data platforms and big data pipelines
“Data engineer focused on building reliable, production-grade pipelines and external data collection systems on AWS (S3/Lambda/SQS/Glue/EMR) using PySpark/SQL, serving curated datasets to Snowflake/Redshift for finance and fraud teams. Has operated a large-scale crawler ingesting millions of records/day with anti-bot tactics, schema versioning/quarantine, and CloudWatch/Datadog monitoring, and also shipped a versioned REST API with caching and query optimization.”
Nikitha Margadi
Mid-level Data Engineer specializing in cloud lakehouse, streaming, and MLOps
“Data engineer at AT&T focused on large-scale telecom (5G/IoT) data platforms, owning end-to-end pipelines from Kafka/Azure ingestion through Databricks/Delta Lake transformations to serving analytics and ML. Has operated at very high volumes (~50+ TB/day) and delivered measurable performance gains (25–30% faster processing) plus improved reliability via Airflow monitoring, robust data quality checks, and resilient external data collection patterns (rate limiting, retries, dynamic schemas).”
Jareena kowsar shaik
Mid-level Machine Learning & GenAI Engineer specializing in LLMs, RAG, and NLP
“Built and deployed an LLM-powered customer support assistant (“Notable Assistant”) focused on automating common post-customer queries while maintaining multi-turn context and meeting scalability/latency needs. Experienced with production orchestration and operations using Kubernetes and Apache Airflow (DAG-based ETL, scheduling, monitoring/alerts), and has partnered closely with customer service stakeholders to align chatbot behavior with brand voice through iterative testing.”
Bharath TVS
Senior Data Scientist specializing in NLP, LLMs, and Computer Vision
“Applied NLP/ML engineer with experience at KeyBank and Novartis building production document intelligence and entity-resolution systems in finance and healthcare. Has delivered end-to-end pipelines (Airflow + AWS) using transformers (DistilBERT/Sentence-BERT), vector search (FAISS/Milvus/Pinecone), and human-in-the-loop labeling to achieve measurable gains (40%+ faster queries; up to 88% F1 and 93% precision/90% recall in entity linking).”
Ramya Latha
Senior AI/ML & Data Engineer specializing in Generative AI and RAG systems
“GenAI/RAG engineer who has deployed a production policy/regulatory search assistant for a financial client using LangChain + Vertex AI, FastAPI, Docker/Kubernetes, and Airflow-orchestrated data pipelines. Demonstrated measurable impact with 50–60% latency reduction and 70% fewer pipeline failures, plus KPI-driven grounding evaluation (90%+ target) and strong cross-functional collaboration with compliance/business teams.”
Mid-Level Software Engineer specializing in backend, cloud, and AI/LLM systems
Mid-level AI/ML Engineer specializing in NLP, recommender systems, and Generative AI
Mid-level AI/ML Engineer specializing in Generative AI and LLM solutions
Senior Machine Learning Engineer specializing in agentic systems, RAG, and edge AI
Mid-Level Data Engineer specializing in scalable cloud data pipelines and API-driven data services
Mid-level Data Engineer specializing in financial risk, compliance, and real-time streaming
Mid-level Machine Learning Engineer specializing in NLP, Computer Vision, and LLMs
Mid-level AI/ML Engineer specializing in LLMs, RAG systems, and MLOps
Mid-level AI/ML Engineer specializing in RAG, LLMs, and MLOps for finance
Mid-level Data Engineer specializing in cloud-native data pipelines and streaming
Senior Full-Stack Software Engineer specializing in Healthcare IT and cloud migration
Mid-level Machine Learning Engineer specializing in GenAI and scalable ML pipelines
Mid-level Backend Engineer specializing in .NET healthcare and medical imaging systems
Mid-level AI/ML Engineer specializing in LLMs, NLP, Computer Vision, and MLOps