I build practical Salesforce automation, reporting, data workflows, and custom tools around the way teams actually work—not the other way around.
Available for project-based work, fractional administration, and subcontract support. I can work independently or closely with your team to understand the process behind the request and build something people will actually use.
Record-triggered automation, business logic, configuration, process improvement, troubleshooting, and user-centered CRM design.
Useful reporting structures that turn operational data into clear pipeline, performance, and workflow visibility.
Data cleanup, transformation, imports, Excel systems, Python-assisted workflows, matching, deduplication, and structured CRM-ready outputs.
Examples are intentionally anonymized and use fictionalized data. They demonstrate the structure and type of solutions I've built without exposing employer, client, or proprietary information.
Designed an automated process that applies configurable deal logic, calculates fees and multi-agent splits, updates related records, and feeds the resulting data into centralized reporting.
Explore the workflow →
Reduced setup work by making proposal type the trigger for a standardized downstream workflow. Required marketing fields are set automatically and the team gets one editable pipeline for tracking progress.
See the process →Built Python workflows that connect with CRM data, transform external datasets, perform record matching and deduplication, handle insert/update logic, and generate structured outputs for downstream use.
See the approach →
Led the implementation and production release of a two-part engagement feature that rolls external prospect activity into Deal and Contact records, giving brokers one place to see who is engaging and what they are looking at.
Read the case study →A connected system that moves from deal inputs through calculation logic and related records into useful team reporting.
Multi-scenario calculations and split structures created repetitive manual work and made consistent downstream reporting harder.
Record-triggered automation applies business rules, calculates values, supports multiple split scenarios, and updates the records that reporting depends on.
A repeatable calculation process with clearer data lineage and reporting that updates from the same underlying records.
The user experience stays simple: create a new deal record and select the proposal type. The system handles the setup behind the scenes.
Python is most useful when it removes the tedious middle steps between source data and the system where people need to use it.
Clean and reshape external data into consistent structures suitable for CRM workflows and analysis.
Use repeatable matching logic to distinguish new records from existing records and reduce duplicate creation.
Create structured insert/update outputs and location-based data exports without repetitive manual preparation.
A production Salesforce feature that consolidates prospect engagement from listing and email platforms into the Deal and Contact records brokers already use.
Buyer and tenant engagement signals were spread across external listing and email tools, forcing brokers to cross-reference platforms to understand which contacts were actively engaging with a listing.
Implemented two Salesforce record-page experiences: a Deal-level engagement summary that ranks engaged contacts, and a Contact-level rolled-up view showing which deals each prospect has interacted with by source and recency.
The feature is live in production, giving brokers a consolidated engagement view inside Salesforce while also removing obsolete legacy code that had become a blocker for future Apex releases.
The production deployment exposed an org-wide Apex code-coverage issue. I used Salesforce code-coverage data through the Tooling API to trace the gap to long-unused Customer Portal Apex classes and associated Visualforce components that were sitting at 0% coverage.
After confirming the legacy functionality was not in use, I validated the dependency cleanup in sandbox and safely retired the obsolete components with a Metadata API destructive-changes deployment. I then worked through separate deployment blockers involving a validation rule, an unused Flow, and test-data failures before completing the production release.
Before moving into Salesforce administration, I worked as a CRM user in sales. That perspective still shapes how I approach technical work: a solution isn't finished just because it functions—it should also make sense to the people expected to use it.
My work spans Salesforce administration, Flow automation, reporting, data management, Excel tooling, and Python-assisted workflows. I’m available for focused projects, ongoing fractional support, and subcontract work with consulting teams.
Industry experience: Real Estate · Financial · Construction · Utilities
I have hands-on experience working with complex real estate, financial, construction, and utility data, including operational records, financial calculations, reporting, data transformation, and CRM process automation.