Data & Software Engineer
I’m a developer working across data engineering, backend systems and applied AI. Turning complex problems into useful, reliable solutions.
Every skill here is tied to real work. Pick one to see where it made a difference.
How I use it: My main language — production data pipelines, a Flask service at work and the AirMood assistant.
Earth observation, closer to people.
A voice-enabled assistant connecting air quality, weather and satellite data to everyday decisions.
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Different problems. The same curiosity to understand, build and improve.
A backend for getting things done.
A productivity API with authentication, authorization and a layered TypeScript backend.
Earth observation, closer to people.
A voice-enabled assistant connecting air quality, weather and satellite data to everyday decisions.
A broader picture of water quality.
A multimodal pipeline combining water samples, Landsat imagery and climate data for water-quality modeling.
From industrial processes to software and data, learning by solving real problems.
Production data pipelines, backend integrations and tooling for the Databricks ecosystem.
Built and maintained 20+ batch jobs with PySpark, SQL, Delta Lake and Unity Catalog. Migrated an approximately 20-notebook pipeline to serverless Lakeflow/DLT, reducing runtime from about 30 to 8 minutes.
Built and deployed a Flask/Pydantic service to process RFID readings, apply business rules and update MongoDB and SQL Server, running in Docker on a VM.
Built Python tooling for versioning and promoting Genie metadata. Reduced LLM output cost by 75% in a cataloging pipeline and added primary/fallback model routing.
Practical foundations in Python, PySpark, Databricks and industrial data.
Worked with notebooks, Bronze/Silver data layers, analysis and Git. Explored Prophet and LSTM time-series proofs of concept during the transition to a development role.
Academic education, verifiable credentials and continued study.
At Univates, I connect my software engineering studies with backend development, data engineering and collaborative projects.
Cloud engineering · Google Cloud
Workflow orchestration · Apache Airflow 3
Cisco Networking Academy
Red Hat Training
HackerRank · skills assessment
Databricks Academy · exam preparation
Choose a focus and a language. Both versions tell the same story, through a different lens.
The document language is independent of the website language.
Data Engineer | Databricks | Applied AI
Data Engineer with production experience in the Databricks ecosystem, working daily with PySpark, SQL, Delta Lake, Unity Catalog, and Asset Bundles. Builds and maintains batch pipelines, platform automation, and applied AI solutions. Has worked across 20+ Databricks jobs, migrated an approximately 20-notebook pipeline to Lakeflow Pipelines/DLT reducing runtime from about 30 to 8 minutes, and reduced LLM output cost by 75% in a production pipeline.
