Ali Hamza Detho

I'm a data engineer with around three years of experience building and advising on cloud data solutions, primarily on Azure with a GCP background. My work spans production ETL pipelines, dimensional data modeling, and lakehouse architectures, and I've advised client engineering teams on Azure Databricks pipelines (medallion architecture and idempotent upserts) for manufacturing and after-sales data. I care about pipelines that are reliable and measurable: past work includes cutting model-serving latency 60x, speeding up pipeline runs by roughly 80%, and saving a client quality team 20+ engineering hours a week.

Alongside delivery, I develop and technically review data engineering content, hands-on labs, and capstone projects across Databricks, Snowflake, dbt and Power BI. I'm a heavy Claude and Claude Code user, producing drafts with AI and reviewing them closely for technical accuracy and clarity before release. That mix of hands-on engineering and AI-assisted workflows is where I'm focused now, as I move deeper into Gen AI and agentic engineering.

I've spent my whole career working remotely with distributed, international teams, so I'm comfortable communicating technical trade-offs clearly to both engineers and non-technical stakeholders. My hours give full overlap with US Eastern and all of European business hours, which makes async-plus-realtime collaboration straightforward. I'm looking for a remote role where I can own work with visible, measurable impact and keep learning from experienced engineers.