Enterprise SaaS Data & Analytics Platform
Designed, built, and maintained an enterprise data and analytics platform from the ground up in AWS Redshift, integrating Salesforce, NetSuite, HubSpot, and product/platform data. Developed analytics-ready data models supporting revenue, customer, product usage, marketing, finance, and executive analytics.
Built the engineering ecosystem around the platform, including dbt transformations, automated data quality and reconciliation, Airflow and Prefect orchestration, CI/CD, Tableau analytics, and governed business metrics.
Stored Procedures in dbt
Designed a pragmatic migration bridge for executing existing database stored procedures inside a dbt-managed environment, enabling incremental modernization instead of requiring an all-at-once rewrite.
Airflow & Prefect Orchestration
Built parameterized Airflow and Prefect workflows for warehouse and dbt workloads, with configurable execution, failure handling, monitoring, and deployment controls.
CI/CD & Deployment Engineering
Built state-aware dbt deployment workflows and a practical pattern for automated pre- and post-deployment SQL when production changes require operations outside normal dbt models.
Data Trust & Audit Analytics
Used audit dimensions, reconciliation, and Tableau exception dashboards to make data-quality issues visible, trace them to operational records, and support correction at the transactional source rather than hiding problems downstream.
ARR Metric & Revenue Analytics
Engineered traceable ARR logic around messy real-world contract dates, late renewals, overlaps, backdated changes, expirations, and cancellations — replacing opaque manual calculations with governed revenue analytics.
Data Profiling
Built profiling tools and a practical data-archaeology approach for discovering useful, trustworthy data through distributions, null patterns, uniqueness, relationships, staleness, and other structural signals.