Bridging aviation domain expertise with data-driven engineering
Mechanical Engineer (Aviation Transport) with hands-on TSE experience at SmartLynx Airlines and AMAC Aerospace, working across Airbus and Boeing fleets in EASA Part-M and Part-145 regulated environments.
I combine deep aviation domain knowledge — AD/SB forecasting, WQAR monitoring, airworthiness compliance, MRO operations — with applied data analytics skills in SQL, Python, and BI tooling. My goal is to work at the intersection of both: using data to solve real aviation engineering and operational problems.
Recently completed my MSc in Mechanical Engineering (Aviation Transport) at Riga Technical University, with a thesis applying classical fault detection methods to aircraft air data sensor data using simulated flight data.
📍 Riga, Latvia · 🇪🇺 Valid LV work authorisation until 12/2026 · Open to relocation across EU & UK
Languages & Data
BI & Visualisation
Product & Web Analytics
Aviation Systems
| Focus | Description | Stack |
|---|---|---|
| 📊 Data Analytics Course | Completing the final capstone projects — applying SQL, Python, and BI to real product and financial analytics problems | Python SQL Tableau |
| 🛫 Aviation Analytics | Extending my portfolio into aviation-specific case studies — on-time performance, MRO KPIs, and operational reliability | Python SQL Power BI |
Riga Technical University · MSc Mechanical Engineering (Aviation Transport)
Classical fault detection methods (threshold-based and rate-of-change) evaluated against bias and freeze faults across simulated airspeed sensor data. 600 Monte Carlo runs across varying noise levels and flight phases (climb/descent).
Key results: Both detectors caught bias faults almost instantly with zero missed detections. For freeze faults, the rate-of-change detector caught every case (~5s delay) while the threshold method missed them entirely at low-to-medium noise — a clear, safety-relevant finding.
Python MATLAB Signal Processing Monte Carlo Simulation Fault Detection
| # | Project | Tools | Focus |
|---|---|---|---|
| 01 | SQL Database & Marketing Analytics | SQL BigQuery PostgreSQL |
ROMI, gaps-and-islands, GA4 funnel |
| 02 | SaaS Funnel Dashboard | Power BI Tableau |
Live currency API, supply chain lead time |
| 03 | Product Tracking Architecture | Amplitude Excel |
Event taxonomy, TTFV mapping |
| 04 | GA4 E-commerce Conversion Funnel | BigQuery SQL Tableau |
7-step funnel, drop-off analysis |
| 05 | SaaS MRR & Retention Analytics | PostgreSQL Tableau |
MRR decomposition, churn dynamics |
I managed @airfighters on Instagram — an aviation community of 430K+ followers focused on aviation photography.
"Aviation data is a different language. I speak both."