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Марк

Інженер даних

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Інженер даних, ІТ-спеціаліст 
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Mark Slipenkyi
Gdańsk, Poland | [open contact info](look above in the "contact info" section)
[open contact info](look above in the "contact info" section) LinkedIn GitHub Site Apify

Experience Personal Projects
LSN SP. Z O.O. Aug 2025 – Sep 2025 3City Transit — Real-Time Transit Analytics
Data Engineer Lakehouse Kafka, Spark, Delta Lake, Airflow, Go, DuckDB
• Managed a production data lake for an insurance company, • Built an end-to-end streaming lakehouse for Gdańsk’s transit
cleaning and extracting raw, sensitive information from numerous network
client forms • Go/Kafka ingestion of live GTFS-RT feeds, streamed via Spark
• Performed customer segmentation using embeddings, modelling into a Delta Lake medallion architecture with Airflow quality gates
with NumPy/Pandas/SciPy and visualising results interactively in • Served through a Go/DuckDB read API behind a React dashboard
Plotly
• Built an AI agent (CrewAI, LangChain) with schema-level access
Zhuch — Neuroevolution-Trained Multiplayer Tank
to the data lake, enabling rapid exploration and experimentation
Arena Go, Python, MLflow, Kafka, Spark, Prometheus, Terraform,
Helm
FERRET-LABS Oct 2025 – Sep 2026
Data Engineer • Built a full MLOps loop around a neuroevolution training system
• Deterministic headless Go arena (CI-parity-tested against Python)
• Own the production backend and underlying data model for Saqla, with MLflow experiment tracking and an Elo-gated promotion
a live surplus-food marketplace — designed the schema powering pipeline
listings, inventory, and transactions across multiple businesses in
• Kafka/Spark/Prometheus telemetry across a
Uzbekistan
Terraform+Helm-deployed stack
• Built and operate the Java/Spring service end-to-end, including
migrating both the application and its data layer from AWS to
Railway as ops needs evolved FMCW Radar Simulation & YOLO Dataset Pipeline
• Saqla’s data model supports live expansion into Ukraine and Python, Signal Processing, Computer Vision, YOLO
Kazakhstan markets • Built a classification/detection pipeline generating synthetic,
auto-labelled radar training data end-to-end, from waveform
AVTOPAZL Jan 2023 – Sep 2026 modelling to a YOLO-ready dataset
Data Engineer • Delivered as a Bachelor’s thesis project, graded 5.0/5.0

• Designed the schema and infrastructure for a private
automotive-components data warehouse OrniWatch — Passive Bird Species Detection via
• Built and scheduled recurring scraping jobs against proxy-backed CRNN Python, Deep Learning, Audio Signal Processing
infrastructure to keep the warehouse continuously up to date • Built and tuned a CRNN classification model detecting bird
• Ran deep analysis on the resulting data to track market pricing vocalizations in long-form audio recordings
• Handled extreme label sparsity (~0.005 positive-label fraction)
through targeted data handling and model tuning
Education
GDAŃSK UNIVERSITY OF TECHNOLOGY Gdańsk, Popout — Podcast-to-Reels Platform Next.js, FastAPI,
Poland Celery/Redis, PostgreSQL, Anthropic Claude API, ElevenLabs, ONNX
B.Eng. Data Engineering 2022 – Feb 2026 • Built an async, LLM-driven podcast-to-reels pipeline
• Final Grade: 4.5/5.0 (Thesis: 5.0, Final Exam: 5.0) | GPA: 4.2/5.0 • Claude API scores every transcript segment across five virality
• Coursework: Big Data Processing, Data Warehousing, ML & AI, dimensions (hook, curiosity, emotion, controversy, storytelling)
Cloud Dev (C++, Java, Python) • A shot-aware YOLO/ONNX face-detection stage drives auto-crop
for vertical video, running on a Celery/Redis job queue so a
multi-hour episode never blocks the UI
Volunteering
PLAST (UKRAINIAN SCOUTING), GDAŃSK Technical Skills
Event Coordinator Data Engineering / Big Data: Spark, Kafka, Hadoop, Airflow, Neo4j,
• Managed strategic scouting routes and coordinated outdoor Redis, MongoDB
Data Science: NumPy, Pandas, SciPy, Plotly
training camps (vyshkoly)
Languages: Python, Java, C/C++, Go, Rust, SQL, R
Backend / Web: FastAPI, Node.js, Next.js, Spring, TypeScript
YASKRAVO, RIVNE AI / LLM: CrewAI, LangChain, prompt design, embeddings
Volunteer Infra / Cloud: Docker, AWS, Railway, GitLab CI
Other: Selenium, WebAssembly, Data Warehousing (VS Data Tools, Hive)
• Organised community music events and a charity tour that raised
$1,000+ Languages
Ukrainian (Native) · English (Fluent) · Polish (Fluent) · Russian (Fluent)
· Chinese (Elementary)

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