Available for opportunities

Hi, I'am Saurav Karki

Data Engineer | US Healthcare Specialization | Microsoft Certified: Fabric Data Engineer Associate

Engineer adept at constructing resilient data infrastructure and executing streamlined data pipelines, enabling me to extract valuable insights from extensive datasets.

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Data Pipelines ETL / Airflow

Cloud & Big Data AWS · Azure · Spark

4+ Years experience

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01 — About

A bit about me

Data Engineer with over 4 years of experience across cloud services and big data technologies including AWS, Azure, Spark, DBT and RDBMS. I work in the US healthcare domain to create, maintain and monitor healthcare-based data products. Highly proficient in Python, PySpark and SQL, with a deep understanding of data warehousing, relational database systems, and transforming data through robust ETL/ELT workflows — along with hands-on expertise in BI tools (Apache Superset and Looker Studio) and web scraping.

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0 + Years experience

0 + Completed certifications

0 + Companies worked

What I focus on

Resilient data infrastructure
ETL/ELT pipelines on AWS & Azure
US healthcare data products
BI & data visualization

02 — Skills

Technical skills

Data Engineer

Cloud · Big Data · ETL/ELT · Analytics

Languages

Python
C / C++
SQL
Flutter

Cloud & Deployment

AWS EC2
AWS S3
AWS RDS
AWS Lambda
AWS Glue
Athena
Azure Synapse
ADLS Gen2
ADF
Databricks

Databases

MySQL
PostgreSQL
MS SQL
MongoDB
BigQuery
Azure Database

Big Data & Processing

PySpark
DBT

Data Warehousing

Amazon Redshift
Snowflake

Orchestration

Apache Airflow

Visualization & BI

Apache Superset
Looker Studio

Web Scraping

Selenium
BeautifulSoup

Developer Tools

Git
Docker
VS Code
Visual Studio
PyCharm

Framework

Flask

03 — Journey

Experience & Education

Work April 2025 — April 2026

Data Engineer‑II

Cedar Gate Technologies · Lalitpur, Nepal

Built ETL pipelines to extract and transform data with Cedar Gate's in-house tools into client-specific formats.
Validated eligibility, pharmacy and medical claims data for compliance with US healthcare standards before release.
Collaborated with Data QA teams on analysis reports and mentored junior engineers.

Work August 2022 — March 2025

Data Engineer

Fusemachines Nepal · Kathmandu, Nepal

Designed, built and maintained ETL solutions loading data from multiple sources into a warehouse / data lake.
Used AWS (S3, Athena, EC2, Glue) and Azure Synapse with PySpark for large-scale data transformation.
Built a data-masking pipeline to encrypt sensitive data during prod-to-dev migration; automated and monitored pipelines.

Work August 2022 — Jan 2023

Data Engineer Trainee

Fusemachines Nepal · Kathmandu, Nepal

Performed ETL, data analysis, cleaning and transformation using SQL, Python, PySpark, AWS and Looker.
Gained hands-on experience with Snowflake, Databricks, Azure Synapse and Superset.

Education Nov 2016 — July 2021

Bachelor of Engineering in Computer Science

Nepal Engineering College, Pokhara University · Changunarayan, Nepal

04 — Services

What I offer

Data Engineering

Maintaining data warehouses, managing databases and applying statistical techniques to unlock insight.

Data Engineering

Assiting both personal and commercial clients with financial questions and needs.
Maintaing and extracting data from Data warehouse.
Managing the Database systems
Systematically applying statistical and logical techniques.

ETL / ELT

Designing scalable ETL/ELT pipelines that extract, transform and load data from multiple sources into warehouses for analytics.

ETL / ELT Pipelines

Extracting data from diverse sources — APIs, databases and files — into a central store.
Transforming and cleaning data with PySpark and SQL into analytics-ready datasets.
Loading data into warehouses and lakes following medallion architecture.
Orchestrating and automating pipelines with Airflow for reliable, scheduled runs.

Cloud Computing

Building scalable data infrastructure on the cloud, leveraging AWS and Azure services to run pipelines and analytics workloads reliably.

Cloud Computing

Deploying pipelines and workloads on AWS (EC2, S3, Glue, Athena, Lambda) and Azure (Synapse, ADF, ADLS Gen2).
Building scalable, cost-efficient storage and compute for large datasets.
Integrating cloud tools (Airflow, Airbyte, Superset) into a unified data platform.
Migrating and troubleshooting environments from development to production.

Data Analytics

Transforming raw data into analytics-ready datasets and turning them into clear, actionable dashboards with BI tools.

Data Analytics

Cleaning, transforming and modeling raw data into analytics-ready datasets.
Building business metrics with SQL to drive actionable insight.
Designing interactive dashboards and reports using BI tools (Apache Superset & Looker Studio).
Visualizing trends and KPIs to support data-driven decisions.