Work

Engineering work

Depth over breadth: the problem, the architecture, the tradeoffs, and what I learned. tickvault is the flagship — below it are sanitized case studies from enterprise consulting work.

Flagship · Market Data Warehouse
Flagship View Live →

tickvault

Real system, verified against real data. The live demo above runs against a bounded public export — the full repo is still private.

SQL Server Python Dagster dbt DuckDB FastAPI Streamlit

Problem

A market data warehouse built on a working ingest pipeline (SQL Server), proving the data is trustworthy: correct under messy input, corrections, and reruns, with full lineage from source to backtest result. Covers EUR/USD and GBP/USD minute bars, 2015–2026 (~7.9M bars each).

Architecture

Medallion pipeline (Dagster + dbt + DuckDB). Bronze: immutable, run-addressed Parquet files per symbol/day with an active/superseded manifest. Silver (dbt): reprocesses through that manifest so reruns never double-count; corrections are versioned, not overwritten. Gold: the stable published table. A monitoring layer flags gaps/anomalies automatically. Served via FastAPI and a Streamlit dashboard, with a live-feed mode.

Key decisions & tradeoffs

  • Public demo runs DuckDB-WASM against a real, bounded data export — real SQL, zero hosting cost, at the cost of showing only a slice.
  • Corrections are tracked via an active/superseded manifest, never an overwrite — every correction is a provable, queryable event.
  • Dagster CLI is blocked from writing to the real database after it silently overwrote backfilled data three times; backfill/live-feed scripts are now the only supported path for real data.

What I learned

  • Driving a real browser caught bugs code review alone missed.
  • A passing CI badge isn't proof a check ever ran — found a CI bug that had silently broken the idempotency check since the first commit.
Healthcare Technology · 18-month project

Healthcare Data Platform Modernization

Challenge

A large healthcare organization needed to modernize legacy data extraction and reporting processes. Operational teams lacked self-service analytics and had to rely on slow, manual data prep.

Approach

  • Designed and implemented secure RESTful API integration for multiple source systems.
  • Automated ETL pipelines to handle complex data transformations at scale.
  • Built interactive dashboards for operational and leadership use.
  • Implemented data validation and QA to ensure compliance-grade accuracy.

Impact

  • Reduced data prep cycle from hours to minutes.
  • Enabled real-time, self-service analytics.
  • Improved reporting accuracy and consistency.
  • Eliminated manual intervention in critical workflows.

Technologies

.NET Framework SQL Server REST APIs SSIS Power BI
Process Automation · 12-month project

Enterprise Workflow Automation

Challenge

A large enterprise struggled with manual workflows, departmental silos, and limited visibility into process status, leading to inefficiencies and compliance risks.

Approach

  • Analyzed existing processes and identified automation opportunities.
  • Implemented Power Automate workflows for approvals, notifications, and escalations.
  • Integrated SharePoint for document management and collaboration.
  • Built dashboards to monitor workflow performance and compliance.

Impact

  • Reduced manual processing time by 60%.
  • Improved compliance tracking and audit readiness.
  • Increased cross-departmental collaboration.
  • Provided leadership with real-time process visibility.

Technologies

Power Automate SharePoint Power Apps SQL Server REST APIs
SaaS Development · 8-month MVP

Automated Quoting Platform

Challenge

An organization needed a scalable quoting system capable of handling complex configurations and dynamic pricing, while integrating AI for optimization.

Approach

  • Designed cloud-native architecture using microservices.
  • Implemented API-first design for future scalability.
  • Integrated machine learning services for quote optimization.
  • Built a responsive web app to streamline the quoting workflow.

Impact

  • Reduced quote generation time from days to minutes.
  • Improved accuracy and consistency of pricing.
  • Enabled data-driven optimization of quotes.
  • Established foundation for future automation and reporting.

Technologies

FastAPI React Firestore GCP Cloud Run Vertex AI
Data Integration · 6-month project

Large-Scale Data Migration

Challenge

An enterprise needed to migrate data from multiple proprietary legacy systems while maintaining strict data integrity and minimizing downtime.

Approach

  • Built custom API integration layer to extract and normalize legacy data.
  • Designed resilient ETL pipelines with error handling and logging.
  • Implemented data validation frameworks for accuracy and compliance.
  • Established monitoring and alerting for data quality.

Impact

  • Successfully migrated 28M+ records with 99.9% integrity.
  • Zero downtime during migration window.
  • Delivered reusable migration framework for future projects.

Technologies

Python SQL Server REST/SOAP APIs Apache Airflow Docker