I help teams replace manual reporting, scattered workflows, and unreliable data processes with automated, documented systems.
I'm Jiyoung Roh, a Data Systems & Automation Consultant. I can sit with stakeholders, understand where reporting or workflow is breaking down, and then build the Python/SQL pipeline, automation workflow, or reporting system that fixes it.
Most of my work starts the same way: a team has outgrown its spreadsheets, reporting is fragmented, or someone is spending 10 hours a week on something that should take 10 minutes. I help clarify whether the right solution is a dashboard, an automation workflow, a data pipeline, or simply a cleaner process — then build it.
I understand the business problem and can implement the technical solution — no translation layer needed.
Everything I build comes with documentation. Your team should be able to maintain it after I leave.
Available via Upwork, direct freelance, or consulting engagements.
Your team is copy-pasting between spreadsheets, manually processing PDFs, or running the same query every Monday. I automate it.
Reports live in 5 different places, nobody trusts the numbers, and leadership keeps asking for 'one source of truth.' I build that.
Data needs to move from point A to point B without breaking, losing rows, or requiring someone to babysit it. I build the pipeline so it runs reliably.
A process that made sense for 3 people doesn't work for 30. I map what's breaking, cut the unnecessary steps, and rebuild it to scale.
You're outgrowing Google Sheets but not ready for a full data team. I set up the warehouse, the pipelines, and the BI layer so you don't have to.
A Canadian fitness chain with 50+ locations had no unified reporting. I built a BigQuery reporting layer, set up Apps Script refreshes to keep data current, and delivered Looker Studio dashboards for cross-location visibility.
A U.S. insurance firm was manually keying data from hundreds of claim PDFs weekly — multiple formats, inconsistent layouts. I built Python extraction with regex/parsing logic to handle each format, then piped structured output into Excel VBA for downstream use.
A U.S.-based workforce intelligence platform needed to go from raw, high-volume datasets to self-serve analytics. I built a DuckDB + Parquet processing workflow, created curated reporting layers, and connected the outputs to Metabase for self-serve BI.
HYBE needed to move a large volume of legacy data into a more reliable structure. I supported the migration through data cleaning, workflow automation, and validation design to improve consistency and reduce operational risk.
Real numbers from real projects — not hypothetical benchmarks.
BigQuery + Apps Script + Looker Studio workflow replaced 10+ hrs/week of manual reporting
DuckDB + Parquet + Metabase workflow built for high-volume analytics and self-serve reporting
Automated migration and validation workflow built for a complex legacy data transition
Python + regex parsing automated multi-format PDF data entry and reduced manual errors