About
A data profile at the intersection of engineering, analytics, and ML
I focus on building data products that are reliable enough for engineers and clear enough for decision-makers.
My work spans modern data platforms, analytical modeling, executive dashboarding, automation, and machine learning operations. The portfolio is structured around case studies so each project can show context, architecture, decisions, and business impact.
Designing cloud data platforms with clean layers, orchestration, and observability
Turning ambiguous business questions into trusted metrics and dashboards
Building practical ML workflows with reproducibility and deployment in mind
Communicating trade-offs clearly across engineering, analytics, and leadership
Tooling
Comfortable across the data lifecycle
Data Lifecycle Stack
From ingestion and transformation to dashboards, ML, and deployment.
Python
AWS
BigQuery
GCP
dbt
Airflow
Spark
Power BI
Docker
GitHub
MLflow
SQL
Python
AWS
BigQuery
GCP
dbt
Airflow
Spark
Power BI
Docker
GitHub
MLflow
SQL