Data Engineering · AI Systems · Analytics

Rachel L.

I engineer data pipelines, analytics systems,
and AI-powered tools that make operations
measurably faster and more reliable.

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SQL· Python· Microsoft Fabric· Power BI· React· Gemini AI· PostgreSQL· Delta Tables· Apache Spark· TypeScript· FastAPI· REST APIs· Azure· Medallion Architecture· SQL· Python· Microsoft Fabric· Power BI· React· Gemini AI· PostgreSQL· Delta Tables· Apache Spark· TypeScript· FastAPI· REST APIs· Azure· Medallion Architecture·
About
Languages & Query
SQL Python TypeScript
Cloud & Data Platforms
Microsoft Fabric Power BI Apache Spark Delta Tables Azure
Frameworks & Tools
React FastAPI PostgreSQL
Systems & AI
Gemini API OpenAI API REST APIs Claude Code

Systems builder.
From both sides.

I engineer data pipelines, analytics systems, and AI-powered tools that make operations measurably faster and more reliable. Focused on SQL analytics, API-driven systems, and support tooling — building the data layer that powers better decision-making.

My background in technical support and operational analytics means I approach data problems differently — I've debugged API failures, traced delivery errors, and built the dashboards that catch issues before they escalate.

Open to Data Engineering, Support Engineering & Analytics Roles

Available for data engineering, support engineering, and technical operations roles. I build robust systems, debug them when they break, and create the visibility that prevents it from happening again.

Projects

Featured Work

01
Microsoft Fabric Power BI Spark Delta Tables Medallion Architecture Python
End-to-EndLakehouse Pipeline
Bronze → GoldMedallion Architecture
Real-TimeSLA Alerting
GitHub

Webhook Delivery Monitoring

Microsoft Fabric Medallion Lakehouse & Power BI Operational Dashboard

Webhook delivery systems need real-time visibility into failure patterns, retry behaviour, and partner reliability — without it, operational teams are blind to cascading failures and SLA breaches before they escalate.

Built an operational webhook monitoring and partner reliability dashboard in Microsoft Fabric using a medallion Lakehouse architecture. Designed Bronze, Silver, and Gold data layers with Spark and Delta tables to ingest, clean, and aggregate webhook delivery data. Developed Power BI dashboards to monitor webhook success rates, retries, partner failure patterns, latency trends, and operational health metrics with threshold-based alerting logic.

Power BI Dashboard
Fabric Notebook
Semantic Model
02
SQL PostgreSQL CTEs Window Functions Data Analysis BI
8 QueriesCTEs & Window Functions
SLA BreachPattern Analysis
Triage & StaffingActionable Insights
GitHub

SQL Analytics Case Studies

Support Operations Analytics, SLA Risk & Workflow Optimisation

Support teams managing high ticket volume across multiple channels often lack visibility into where delays actually happen. This project analyses SLA breach patterns, resolution bottlenecks, and automation opportunities across ticket data — surfacing the operational insights that drive better triage and staffing decisions.

Using SQL and PostgreSQL-style queries, the project analyzes ticket volume, resolution times, customer tiers, support channels, and issue categories to surface operational insights. It highlights trends in SLA performance, workload distribution, and recurring issue types, providing a foundation for better decision-making and process optimization.

Analytics Dashboard
03
React TypeScript Gemini AI PostgreSQL Stripe
Gemini AIResume Rewriting Engine
ATS + HumanDual Optimisation
Stripe + PDFFull-Stack SaaS
Live Demo

Resume Tailor

AI-Powered Resume Optimisation for Every Job Application

Job seekers spend hours manually rewriting their resume for each application, often missing the exact keywords and phrasing that ATS systems and hiring managers scan for — resulting in rejections before a single human reads a word.

Resume Tailor uses Google Gemini AI to instantly analyse a job description and intelligently rewrite your resume to match. It preserves your authentic experience while optimising language, keywords, and structure for both ATS systems and human reviewers. Features include inline section editing, drag-to-reorder, one-click PDF and DOCX export, and a Free → Pro subscription model with Stripe billing and PostgreSQL-backed usage tracking — shipped end-to-end as a full-stack SaaS product.

Upload & Tailor
AI Analysis
Review & Export
04
React TypeScript Voice APIs AI Parsing Local-First Storage
Voice → TaskInstant Capture Flow
Local-FirstNo Account Needed
Low FrictionADHD-Centred UX
GitHub

EchoFlow

AI Voice Planner for ADHD-Friendly Productivity

Traditional productivity tools assume users can pause, organize their thoughts, and manually plan next steps. For people with ADHD, this creates friction — ideas are lost quickly, and task initiation becomes overwhelming.

EchoFlow is a voice-first AI productivity tool designed to close the gap between thought and action. It enables users to capture ideas instantly, structure them with AI assistance, and move into execution with minimal steps. The system combines voice input, AI parsing, and lightweight task organization to reduce cognitive load and improve follow-through. Designed to shorten the path from thought → structure → action, especially for users who struggle with traditional workflows.

Home Screen
Voice Capture
AI Processing
Contact

Have a project in mind?
Let's talk.

Have a project in mind or want to collaborate? Drop me a message.