I'm an Analytics Engineer specializing in the design and implementation of data platforms featuring centralized orchestration, MLOps infrastructure, and secure automation pipelines. I bridge the gap between complex business workflows and high-performance, resilient technical systems that drive measurable strategic impact.
Centralized Orchestration & Infrastructure Deployment of orchestration platforms (Dagster) on dedicated Linux servers to centralize, monitor, and automate critical corporate workflows, reducing operational overhead and standardizing failure monitoring.
MLOps & Automated Forecasting Design and integration of end-to-end MLOps pipelines for autonomous demand forecasting, improving inventory metrics and removing dependencies on legacy third-party ERP architectures.
Data Engineering & Web Scraping Development of optimized extraction pipelines using modern libraries (Polars) and robust web scraping systems (Selenium/Scrapy) to inject real-time market intelligence directly into decision-making environments.
DevSecOps & Governance Implementation of version control standards, code quality frameworks, and AI-assisted agentic workflows (Claude AI) to standardize internal software development and guarantee code alignment.
Infrastructure Security & Migration Restructuring legacy workflows into secure protocols (SFTP/SSH) and transforming full-refresh pipelines into incremental extraction models to optimize performance and information integrity.
While most of my corporate engineering repositories are private, my core achievements focus on building data products end-to-end:
- Autonomous Demand Forecasting Infrastructure: Designed an end-to-end MLOps platform that led to a 30% improvement in forecast accuracy and a 3% stockout reduction for high-priority SKUs.
- Centralized Linux Orchestration Server: Migrated dispersed, manual tracking tasks into a single Dagster instance, automating job control and recovery while optimization saved approximately 4 operational hours weekly per user.
- AgTech Supply Chain Scraping Engines: Built automated data-harvesting pipelines using Selenium and Scrapy to extract complex market pricing structures for immediate strategic raw material negotiation.
- DevSecOps & Secure Pipelines Architecture: Standardized development repositories via GitHub using agentic LLM coding assistant workflows, alongside drafting infrastructure migrations from FTP legacy models to incremental SSH/SFTP environments.
Technical summaries and non-confidential project architecture details can be provided upon request.
Focused on building reliable data systems that create measurable business impact.