Luzaw Shrestha
@luzawshrestha
Experienced Data Engineer & BI Engineer driving real-time, production-ready analytics.
What I'm looking for
I am an experienced Data Engineer and BI Engineer with over six years working across healthcare, insurance, and behavioral analytics, building reliable batch and real-time data pipelines and analytics platforms.
I design and implement scalable ELT/ETL solutions using PySpark, dbt, Kafka, Dagster/Airflow, and cloud data warehouses like Snowflake, Redshift, and BigQuery, and I've reduced costs and improved performance through query optimization and architecture refactors.
I partner closely with ML teams and business stakeholders to deploy ML workflows (SageMaker, MLflow, Azure ML), reverse ETL (Hightouch), and actionable dashboards (Power BI, Tableau, Sigma), driving measurable outcomes such as 30% improved outreach accuracy and 80% reduction in manual KPI work.
I prioritize data governance, security, and observability—implementing HIPAA/GDPR controls, automated tests, CI/CD, and monitoring—and I mentor junior engineers while contributing to cross-functional governance and compliance initiatives.
Experience
Work history, roles, and key accomplishments
Developed scalable ELT pipelines and real-time ingestion using Snowflake, dbt, Dagster, and Kafka, increasing outreach accuracy by 30% and reducing dashboard manual effort by 80%. Implemented HIPAA-compliant governance and automated KPI validation to improve data quality and pipeline reliability.
Migrated petabyte-scale healthcare datasets to AWS and Snowflake and redesigned PySpark Glue jobs and dbt models, improving ETL performance by 60% and BI performance by 50% while ensuring HIPAA/GDPR compliance.
Modernized legacy ETL into dbt + Synapse pipelines and built Kafka + Spark streaming workflows, cutting refresh times by 50% and query costs by 35% while delivering near-real-time dashboards for fraud and retention analytics.
Education
Degrees, certifications, and relevant coursework
University of New Haven
Master of Science, Business Analytics
Completed a Master's in Business Analytics focused on data analysis, modeling, and applied analytics techniques for business decision-making.
Tech stack
Software and tools used professionally
OpenAPI
Amazon Redshift
Airbyte
Fivetran
Azure Synapse
Apache Spark
AWS Glue
Apache Flink
Talend
SAS
Amazon Quicksight
AWS IAM
AWS Step Functions
GitHub
GitLab
Kubernetes
AWS CodePipeline
Jenkins
GitHub Actions
GitLab CI
Salesforce
NumPy
Pandas
PySpark
dbt
Sqoop
PostgreSQL
MongoDB
Cassandra
Hadoop
Vertica
Gmail
Databricks
Redis
Terraform
Azure DevOps
Jira
JavaScript
JSON
TensorFlow
PyTorch
MLflow
scikit-learn
Streamlit
Kafka
Apache NiFi
Apache Pulsar
FastAPI
PagerDuty
Grafana
Prometheus
Datadog
GraphQL
JSON API
Elasticsearch
Azure Functions
pytest
VMware vSphere
Airflow
Apache Beam
Redis Cloud
Google BigQuery
Amazon EMR
SQL
Amazon SageMaker
XGBoost
Mode Analytics
Dagster
Hightouch
Monte Carlo
Delta Lake
Great Expectations
Collibra
Availability
Location
Authorized to work in
Job categories
Skills
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