Hariom Nayani
Data @ SpectraMedix | Health Tech | MS CS, Stevens
- Role
- Analytics Engineer at SpectraMedix
- Location
- Hoboken, NJ, US
- LinkedIn followers
- 500 followers
About Hariom Nayani
Data professional with experience across analytics engineering, data quality, and applied data science in regulated healthcare environments. Currently an Analytics Engineer building and operating large-scale healthcare analytics platforms—designing data pipelines, validating complex datasets, and enabling reliable, decision-critical insights for business and client stakeholders.Strong background in Python and SQL, with hands-on experience building ETL/ELT pipelines, data models, and automated reporting workflows using Airflow, dbt, Databricks, and Spark on Azure. Regularly work with large, messy datasets, focusing on data quality, validation, and analytics-ready transformations that support dashboards and downstream analysis.Domain experience in value-based care (VBC), working with healthcare claims, provider performance, contract-level metrics, and clinical data (FHIR/EMR), supporting analytics tied to quality measures, financial performance, and risk-based contracts.Tech stack: Python, SQL, Airflow, dbt, Databricks, PySpark, Azure, AWS, Pandas, NumPy, Git, SVN, Kubernetes, Docker
Experience
Analytics Engineer
Dec 2023 — Present · East Windsor, NJ, US
Designed, built, and maintained Databricks Gold tables, implementing optimized transformations and data modeling to produce reliable, analytics-ready datasets for 14 Health Plan markets, powering Tableau dashboards, reporting, and downstream analytics• Built and automated 20+ monthly Data Quality Reports (DQRs) using Python, SQL and Excel macros, to enforce data integrity and validate upstream pipelines• Automated previously manual cross-team collaboration to reconcile data across diverse product analytics pipelines, reducing data errors by 10%, improving timely delivery of insights by 15%• Developed Airflow pipelines to automate ETL workflows, incorporating unit tests, version control, and CI/CD, reducing manual effort• Optimized Python ETL/ELT processes and dbt models, improving pipeline efficiency and accelerating delivery of analytics-ready datasets by 15%.• Implemented scalable data models and schema standardization to support downstream analytics, dashboards, and client reporting.
Education
Stevens Institute of Technology
Master's degree, Computer Science
R N PODAR
Primary and Secondary school
2004 — 2016
SVKM's Narsee Monjee Institute of Management Studies (NMIMS)
Bachelor of Technology - BTech, Information Technology
2016 — 2020
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