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Vetted Data & Analytics Professionals in the NYC Metro
Pre-screened and vetted in the NYC Metro.
Popular Titles
Entry-level data engineer specializing in analytics and machine learning
Mid-level Data Engineer specializing in financial data engineering and scalable pipelines
Likitha Reddy Kotla
Mid-level Business Analyst specializing in BI and analytics
“Analytics professional with Dell experience unifying global online sales, web analytics, SAP, and planning data across 20+ countries into scalable reporting pipelines and Power BI dashboards. Stands out for combining deep SQL/ETL work with Python automation, KPI design, and experimentation—delivering measurable outcomes like 80% less manual effort, a 2% conversion lift worth millions, and faster business decision-making.”
Harshitha Parupalli
Mid-level Data Engineer specializing in multi-cloud real-time and batch data pipelines
“Data engineer with healthcare domain experience who owned 100M+ record pipelines end-to-end (Kafka/Kinesis/ADF → PySpark/dbt validation → Spark SQL transforms → Snowflake/Power BI serving). Built production-grade reliability practices (Airflow orchestration, CloudWatch/Grafana monitoring, pytest + contract/regression tests, idempotent ingestion/backfills) and delivered measurable improvements: 35% lower latency and 40% better query performance.”
Kamalesh Ponnivalavan
Mid-level Data Engineer specializing in capital markets post-trade data platforms
“Data/streaming engineer in capital markets who led an end-to-end trade settlement data product (Kafka→MongoDB→data lake) with rigorous data-quality logic and ~$175K first-year operational impact. Also built a low-latency Go-based CME market data engine feeding SOFR curve generation, using MSK on EKS with performance tuning (idempotency, compression, partitioning) to achieve sub-100ms delivery.”
Ram Jayesh Parekh
Junior Data Analyst specializing in ML, NLP, and cloud data pipelines
“Built and deployed a GenAI-powered PhD career intelligence platform at NYU that maps academic backgrounds to career paths and converts long academic CVs into job-ready resumes. Stands out for treating LLM systems as structured production pipelines—combining NLP extraction, embeddings, orchestration, and AWS deployment—to improve recommendation quality and cut resume preparation time by 70%.”
Intern Data Analyst specializing in product, marketing, and business analytics
Mid-level Azure Data Engineer specializing in Databricks lakehouse and Spark pipelines
Principal Cloud Data Engineering Leader specializing in lakehouse and streaming platforms
Senior BI Analyst specializing in analytics automation and financial services
Entry-level Backend Engineer specializing in distributed systems
Mid-level Data Scientist specializing in credit risk and fraud analytics
Mid-level Data Engineer specializing in cloud ETL/ELT and analytics platforms
Intern-level data analyst specializing in healthcare, marketing analytics, and finance
Junior Data Scientist specializing in NLP, fraud detection, and AI/ML systems
Mid-level Data Scientist specializing in AI/ML and Generative AI
Mid-level Data Scientist/Data Engineer specializing in ML, MLOps, and real-time data pipelines
Associate Director / Senior Data Engineer specializing in cloud ETL and marketing data pipelines
Senior Data Engineer specializing in Azure Lakehouse and LLM/ML data platforms
Mid-level Data Analyst specializing in banking and healthcare analytics
Mid-level Data Scientist specializing in healthcare and financial risk modeling
Mid-level Data Engineer specializing in cloud ETL, big data, and analytics