About
Python-focused engineer with experience in automation, APIs, configuration systems, data processing, and internal tooling. Background includes building XML/JSON-based workflows, automating bulk updates with Python, integrating with APIs, and developing projects involving batch data pipelines, validation, transformation, and real-time market data processing. Also experienced using AI tools to accelerate debugging, development, and engineering workflows. Targeting Data Engineer roles focused on Python, ETL/ELT, data pipelines, validation, transformation, and analytics-ready outputs.
Skills
Languages: Python, C#, SQL
Data Engineering: ETL/ELT, batch processing, real-time data processing, data validation, data transformation, analytics reporting
Data Formats: JSON, XML, CSV, Excel
Tools: Git, Postman, Jira, Oracle Agile PLM, Helix ALM, Visual Studio, AI-assisted development tools (ChatGPT)
Systems & Concepts: REST APIs, cloud-based configuration updates, UDP data ingestion, workflow automation, event-driven processing
My Experience
Software & Test Engineer
HID Global — Krakow, Poland
March 2023 – December 2025
Developed and maintained automated tests in C# and Visual Studio within a larger
engineering team. Contributed to configuration-focused testing tied to product behavior, system validation, and release support. Debugged a Linux-based system using command-line Bash tools during testing and issue investigation.
Built domain knowledge in a new test framework and codebase while applying prior
experience from configuration engineering. Supported software quality efforts across product revisions and release cycles.
Senior Product Support Engineer
HID Global — Krakow, Poland
September 2019 – March 2023
Managed end-to-end custom device configuration requests using XML and later JSON-based formats for newer cloud-connected product revisions. Reviewed customer requirements submitted through Oracle Agile PLM and coordinated with pre-sales teams to clarify technical details. Used Postman to authenticate with servers and push validated JSON configurations to cloud-connected systems after review. Troubleshot software and configuration issues through bug tickets managed in Helix ALM. Built Python scripts to automate mass configuration updates for both legacy XML and newer cloud-based JSON workflows. Prepared firmware release packages for production and created review ECRs in Oracle Agile PLM. Organized and tracked incoming requests independently using a Jira Kanban workflow. Trained and mentored new team members after the function expanded beyond a single-owner workflow.
My Projects
Retail Analytics Pipeline | Python, PySpark, SQL, DuckDB, Streamlit, Docker,
GitHub Actions, Airflow
Built a retail analytics data pipeline using Python, PySpark, SQL, DuckDB, Streamlit, Docker, GitHub Actions, and Airflow; automated ingestion, transformation, validation, warehouse modeling, dashboard reporting, and scheduled workflow orchestration. Modeled warehouse-style tables in DuckDB, including fact_orders, dim_date, and dim_customers, wrote SQL analytics queries for revenue, regional, customer-segment, and order-status reporting, and added a PySpark transformation variant to demonstrate Spark-based ETL workflows. Implemented automated validation with Pytest and GitHub Actions, containerized the dashboard with Docker, and exposed pipeline outputs through a Streamlit analytics UI. Used AI tools (ChatGPT) to accelerate debugging, refine SQL queries, troubleshoot pipeline logic, and improve project documentation during development.
Stock Screener / Market Data Pipeline | Python
Built a Python-based market data pipeline to process end-of-day equity data across European exchanges, generating daily master lists and ranked outputs for trading analysis. Ingested source data, standardized ticker/exchange mappings, and produced structured datasets in JSON, pickle, and Excel formats for downstream analysis. Performed data cleaning, validation, and transformation on market datasets, including rolling price and volume z-score calculations used to identify unusual activity. Generated analytics-ready outputs with historical features such as price z-scores, volume z-scores, and forward return comparison fields to support daily screening workflows.
Real-Time Volume Scanner | Python, APIs, UDP
Built a Python-based real-time market scanner that registered ticker/exchange symbols through an API, consumed live L1 market data over UDP, and monitored intraday activity across European markets. Processed live trade messages into rolling per-symbol volume totals and compared intraday activity against average daily volume baselines to surface abnormal volume signals. Automated signal generation into timestamped Excel outputs and persisted raw trade data to JSON for later review and analysis. Structured the scanner around exchange-specific trading hours, symbol mapping, and repeatable daily execution workflows, demonstrating event-driven and low-latency data processing.
TradingSimAPI | FastAPI, PostgreSQL
Built a transaction-safe trading simulator backend using FastAPI, PostgreSQL, and SQLAlchemy. Implemented market-order execution, position tracking, weighted average cost logic, and account balance updates with transactional integrity. Used database transaction controls and precise numeric handling to model correctness-focused backend behavior relevant to trading and financial systems.