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Designing data platforms that turn fragmented systems into reliable insight.

I focus on turning fragmented data workflows into reliable platforms that support clean reporting, operational clarity, and long-term scalability.

View selected workView resumeData Engineer and Platform Engineer
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JP

Data Engineer and Platform Engineer

Jayas Piya

Data engineer building scalable platforms, ETL systems, and analytics workflows across healthcare and operational domains.

Building data foundations teams can trust at scale.

Jayas is a data engineer with experience building scalable healthcare data platforms using Databricks, PySpark, Snowflake, SQL, and modern ETL practices. His work sits at the intersection of platform reliability, interoperability, and measurable business reporting.

Across roles at Abacus Insights Nepal and Techkraft Inc, he has worked on FHIR-based ingestion systems, predictive healthcare models, warehouse-oriented reporting, and query performance improvements. That background makes him especially strong at designing the unseen infrastructure that keeps modern digital products dependable.

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Focus areas

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Project contributions

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Journal entries

Expertise

System Architecture & Expertise

Data engineering

Jayas is a data engineer with experience building scalable healthcare data platforms using Databricks, PySpark, Snowflake, SQL, and modern ETL practices. His work sits at the intersection of platform reliability, interoperability, and measurable business reporting.

Focus area

Data engineering

Focus area

Healthcare interoperability

Focus area

ETL and warehousing

Focus area

Analytics systems

Specialty

Data engineering

Jayas is a data engineer with experience building scalable healthcare data platforms using Databricks, PySpark, Snowflake, SQL, and modern ETL practices. His work sits at the intersection of platform reliability, interoperability, and measurable business reporting.

Specialty

Healthcare interoperability

Across roles at Abacus Insights Nepal and Techkraft Inc, he has worked on FHIR-based ingestion systems, predictive healthcare models, warehouse-oriented reporting, and query performance improvements. That background makes him especially strong at designing the unseen infrastructure that keeps modern digital products dependable.

Selected work

Selected Deployments

Client systems, product decisions, and implementation work this member has directly shaped.

Web Application DevelopmentWorkflow SystemsProduct Design

Central Dental Assistance

Central Dental Assistance

Healthcare and Dental Operations

Central Dental Assistance

An ongoing dental operations platform focused on streamlining assistance workflows, internal coordination, and day-to-day clinical support.

The project is still under development, but it is already moving toward a clearer internal workflow model with better support for repeatable day-to-day operations.

Web Application DevelopmentWorkflow SystemsProduct DesignOperational Support
View case study

IoT and Intelligent Systems Research

Smart Home Intelligence Research

An ongoing research initiative exploring intelligent home workflows, device coordination, and practical automation design.

The initiative is ongoing and currently focused on research patterns, prototyping directions, and practical ways to connect automation logic with real use-case behavior.

ResearchData SystemsMachine LearningAutomation Prototyping
View case study
ResearchData SystemsMachine Learning

Internal / Research Initiative

Smart Home Intelligence Research

Journal

Writing and Insights

Notes, perspectives, and technical thinking connected to the work this member contributes to.

Software Development

Why Businesses Choose a Custom Software Development Company in Nepal

What global clients look for when choosing a custom software development company in Nepal, from technical depth to delivery clarity.

Read article

Legal Technology

What Modern Law Firms Need From Custom Software

Law firm software should support case visibility, document workflows, and internal coordination instead of adding more operational friction.

Read article

AI Systems

Smart Home AI Research: Making Automation More Useful

Smart home AI research becomes more valuable when it focuses on usable automation, coordination logic, and everyday reliability.

Read article

Principles

Engineering Principles

Reliable insight starts with reliable pipelines.

Principle 1

Good data platforms reduce decision noise by making ingestion, transformation, and reporting more structured from the start.

Good data systems make downstream decisions clearer, faster, and easier to trust.

Principle 2

Interoperability work matters because connected systems only become valuable when the data model is reliable enough to support downstream use.

Scalability matters most when the underlying model is already disciplined and maintainable.

Principle 3

Scalable analytics depends on disciplined pipelines, thoughtful warehouse design, and continuous performance tuning as complexity grows.

Fun detail

Enjoys solving messy data problems where the real work is in structure, quality, and interoperability rather than just dashboard polish.

Fun detail

Moves comfortably between warehousing, transformation logic, and business-facing reporting use cases.

Fun detail

Has explored both production healthcare platforms and self-directed data products such as search and retail intelligence systems.

Available for collaboration

Let's build something precise.

Open to data engineering, analytics platforms, and scalable systems work. Based in Kathmandu, Nepal, and open to product, design, and engineering conversations with global teams.