Jiyoung R.

Analytics Engineer & BI Consultant | Python, SQL, BigQuery

I help growing teams replace manual reporting, scattered spreadsheets, and unreliable dashboards with automated data workflows they can trust. Most clients come to me when: • reports are still updated manually every week • data lives across spreadsheets, PDFs, APIs, and dashboards • leadership does not fully trust the numbers • one person on the team is holding the reporting process together manually • the dashboard exists, but the workflow behind it is fragile I’m a Data Automation & BI Consultant with 4+ years of experience building practical reporting systems, analytics workflows, dashboards, and data automation tools for business teams. I’ve worked with global clients across fitness, insurance, media, entertainment, and B2B data. My projects have included ETL pipelines, reporting automation, dashboard systems, Excel/PDF processing, analytics layers, and large-scale data infrastructure. Recent outcomes: • Reduced manual reporting time by 80% for a multi-location fitness business using BigQuery, Apps Script, and Looker Studio • Automated PDF data extraction and Excel/VBA reporting workflows for a U.S. insurance project • Completed a complex multi-department data migration project in 5 months against a 2-year estimate • Built large-scale workforce/lead data infrastructure using Python, DuckDB, Parquet, Metabase, and automated export views What I can help with: • Manual reporting automation • KPI dashboards in Looker Studio, Metabase, or Power BI • Python / SQL data pipelines • Data cleaning, transformation, and validation • BigQuery / database reporting layers • Excel and Google Sheets automation • PDF and document data extraction • GA4/GTM tracking QA and conversion reporting • Workflow documentation and handoff How I work: • I diagnose the workflow before building • I design the data structure before the dashboard • I validate the numbers before handoff • I build in clear phases or milestones • I document the setup so your team can maintain it For messy reporting or automation projects, I usually recommend starting with a paid Data Workflow Blueprint: source review, metric logic, data model, automation priorities, and a phased build plan before implementation. Tools & skills: Python, SQL, BigQuery, DuckDB, Metabase, Looker Studio, Google Apps Script, Excel VBA, Power BI, Snowflake, R If your team is spending too much time copying, cleaning, checking, or rebuilding reports manually, feel free to message me with what is broken, what you have tried, and what needs to work first.