Welcome to my GitHub portfolio. I'm a B2B SaaS RevOps Analytics Engineer specializing in building data-driven revenue intelligence systems that transform organizations from cost-center analytics into revenue-generating operations.

The complete Modern Data Stack for B2B SaaS Revenue Operations

Transforms fragmented data from HubSpot, Stripe, Zendesk, and internal databases into a unified Revenue Center. Features:

• 7-layer architecture with dbt, DuckDB, and MotherDuck
• Health scoring with 3-signal risk model (payment, churn, engagement)
• MRR Waterfall tracking (New, Expansion, Contraction, Churn movements)
• PQL Intent Scoring (HOT/WARM/COLD) for Sales prioritization
• Reverse ETL pushing insights back to HubSpot
• 160+ data quality tests + Dagster orchestration

Business impact: First run identified 23 at-risk accounts worth $87K; CS intervention saved $45K ARR in 30 days.

Tech Stack: dbt | DuckDB | MotherDuck | Dagster | Lightdash | Python

Reusable dbt macros for B2B SaaS Revenue Operations analytics

A focused macro library centralizing RevOps business logic for consistency across transformation models:

• CRM Normalization — Stage mapping, pipeline velocity, field completeness
• Revenue Classification — MRR movement, ARR segmentation, contract normalization
• Subscription Activity — Active status tracking, renewal detection, proximity
• Customer Lifecycle — Cohort assignment, health tiering
• Finance & Quality — Invoice aging, discount rates, data sanity checks

Install via dbt deps and use across any dbt project handling B2B revenue analytics.

Tech Stack: dbt | SQL | Jinja

Full-funnel marketing analytics warehouse tracking ad spend to closed revenue

Maps the entire B2B customer journey from first anonymous ad click to $100K+ enterprise deal:

• 56+ dbt models across staging, intermediate, and marts layers
• Domain validation filtering personal emails to focus on B2B accounts
• Identity resolution mapping floating leads to Virtual Accounts via domain intelligence
• SCD Type 2 tracking of historical CRM changes
• Streamlit dashboard showing KPI tracking, platform efficiency, lead funnel, and data lineage
• Dagster asset orchestration with full pipeline lineage visibility

Tech Stack: dlt | DuckDB | dbt | Dagster | Streamlit | Python

A production-grade A-Series SaaS data playground for testing RevOps analytics

7-layer revenue funnel simulator creating cross-referenced, realistic sandbox data:

• Meta Ads → HubSpot CRM → Stripe Billing → PostHog Analytics → Freshdesk Support → Supabase → Sales Intelligence
• Call transcripts with structured outcomes (closed_won, lost, stalled) and objections
• Full calendar dimension (dim_date) warehouse-ready
• Hybrid architecture combining real-time Flask frontend with daily batch operations
• 12 months of invoice history for cohort and churn analysis

Perfect for testing dbt models, reverse ETL pipelines, and RevOps dashboards on realistic data.

Tech Stack: Python | Flask | HubSpot API | Stripe API | PostHog | Supabase | Pandas

Revenue-Driven Analytics
Every model I build solves a business problem. Dashboards alone don't move revenue; actionable insights do.

• fct_accounts_health → CS intervention before cancellation
• fct_pql_signals → Sales outreach via Reverse ETL
• fct_mrr_waterfall → Accurate board reporting & financial planning
• dim_accounts.is_ready_for_upsell → Expansion workflows triggered automatically

Cost-Effective Modern Stack
$0/month infrastructure cost using DuckDB + free tiers. Proven with production data.

Modular, Testable Code
160+ automated tests. SCD Type 2 snapshots. Full dbt lineage. If it broke, we'd know before stakeholders did.

• E-Commerce Warehouse — Data warehouse for e-commerce analytics
• HR Attrition Analysis — Employee churn prediction
• Logistics KPI Analysis — Performance tracking for supply chain
• PostgreSQL Index Optimization — Database performance tuning
• SQL Collections — Query reference library
• Metrics Library — Centralized business metrics

Building RevOps systems? Need analytics engineering expertise? Open to discussions about:

• Revenue intelligence architecture
• dbt & Modern Data Stack
• B2B SaaS metrics & analytics
• Open-source analytics

Feel free to explore, fork, and adapt these projects for your organization.

Built with precision. Designed for revenue. Powered by data. 📈