Technical Product Partner / Senior Fullstack Engineer

I help startups and product teams turn product ideas, data and APIs into shipped web applications.

My public repositories show the code side of that work: React/Next.js frontends, TypeScript component systems, maps and data visualizations, Python/FastAPI backends, data pipelines, testing workflows and documentation.

Portfolio · Email

• Product-ready frontends — React, Next.js, TypeScript, component systems, UX-focused implementation
• Data products & visual interfaces — dashboards, maps, charts, data stories and geospatial UI
• Backend & API integration — Python/FastAPI, Node.js, REST/GraphQL, typed contracts and API serving layers
• Delivery quality — testing, CI/CD, documentation, handover and maintainable project structure
• Product thinking — translating unclear product/data/API contexts into usable shipped interfaces

Interactive climate data story combining maps, charts, scroll-driven interaction, satellite data and backend/data workflows.

Highlights

• Next.js / React frontend with scrollytelling, charts and map interactions
• FastAPI backend for aggregated climate data
• Data pipelines for NASA/NOAA/OWID datasets
• Documentation for architecture, operations and data workflows

Stack: Next.js, React, TypeScript, GSAP, D3, Recharts, Mapbox, FastAPI, Python, Pandas, Vercel, Railway, GitHub Actions

Air-quality data product that turns distributed sensor data into an interactive map and chart interface.

Highlights

• Mapbox-based air-quality exploration
• PM2.5 / PM10 views with threshold-based visual feedback
• OpenAQ API integration
• E2E and component testing setup

Stack: React, TypeScript, Material UI, Mapbox GL, Plotly, OpenAQ API, Jest, React Testing Library, Playwright, GitHub Actions

Python pipeline and CLI for Sentinel-2 satellite imagery processing around Uummannaq Fjord, Greenland.

Highlights

• STAC discovery and tile loading
• MobilenetV2 UNet cloud masking
• Rule-based ice / water / land classification
• CSV statistics, quicklook overlays, Docker setup and testable pipeline structure

Stack: Python, PyTorch, Pandas, NumPy, Rasterio, odc-stac, Typer, Docker, Ruff, mypy, pytest

Interactive train schedule visualization for complex rail/transit timetable data.

Highlights

• D3-based train graph visualization
• GTFS-based data processing
• Interactive filters and schedule exploration
• Modern frontend and database-backed architecture

Stack: Next.js, React, TypeScript, D3.js, Material UI, Drizzle ORM, PostgreSQL, Supabase

Real-time word-frequency explorer with a microservice backend and WebSocket-based updates.

Highlights

• React frontend
• Node/Express backend services
• Redis-backed word-frequency data
• WebSocket communication
• Docker Compose development environment

Stack: React, TypeScript, Node.js, Express, Redis, WebSockets, Docker Compose

Some of my strongest product work is client work where the code is private. I document selected case studies with product context, screenshots, tech stacks and shipped outcomes on my portfolio:

www.lukaskreibig.dev

Selected case studies include:

• blocks.cloud — B2B FinOps SaaS, onboarding, dashboards, billing, API/BFF integrations
• Floorwell OS — CRM and operations platform, data-heavy workflows and frontend modernization
• Map the Air — air-quality data product with maps, charts and API aggregation
• Arctic Data Story — interactive climate data experience with maps, satellite data and RAG layer

• Product context before implementation
• Type-safe interfaces between frontend, backend and data workflows
• Clear component and state architecture
• UX and performance as engineering concerns
• Testing and CI/CD as delivery guardrails
• Documentation and handover so teams can continue confidently

Remote freelance projects, startup collaborations and selected senior frontend / fullstack / product engineering roles.

Best fit: MVPs, internal tools, data products, dashboards, maps, onboarding flows and visual web applications.