Data Analytics Engineer

Built production-grade Snowflake stored procedures to transform multi-million-row patient-level marketing interaction data into an analytical star schema for campaign attribution and performance reporting.
Owned 4–5 analytical tables and reporting views, partnering with senior engineers and product stakeholders to finalize schema design after EDA and business-logic review.
Wrote 8–10 parameterized stored procedures with logging-table integration and custom exception handling; an early PR became the template used by the rest of the team.
Implemented a 400-line CTE-driven transformation pipeline, reducing reporting-scale tables from millions of rows into BI-oriented aggregates.
Built 4 Power BI dashboards directly and contributed to a 14-dashboard reporting ecosystem supporting in-house marketing analytics.
Developed Azure DevOps pipeline automation for ordered SQL deployment across environments, saving ~60 hours/month across a 5-developer team.
Augmented an internal ETL migration framework using Azure Data Factory, adding new pipelines and transformations across Snowflake, Oracle, Azure SQL, and Azure Blob Storage at 10M+ row scale.
Implemented secure ETL patterns using Azure Key Vault-backed secret resolution and post-migration SQL validation checks.

Stack: Azure Data Factory, Snowflake, SQL, Power BI, Azure DevOps, Azure Key Vault, Azure Blob Storage, Oracle, Azure SQL