Junior Data Analyst · Data Technician — Birmingham, West Midlands, UK
Finance and operations background moving into data. Four years of reconciling records, chasing discrepancies and answering to deadlines taught me the habit that matters most in analysis: check the numbers before you present them, and say plainly when the data does not support the conclusion.
Currently completing a Level 3 Data Technician bootcamp with LeepTalent — eight weeks across Excel, SQL, Tableau, Power BI, Azure and Python. Every week's work is published below with the evidence attached.
| Repository | Focus | What it demonstrates |
|---|---|---|
| Excel-report | Excel analysis | Structured tables, AVERAGEIF conditional aggregation, SWITCH(TRUE, …) banding, PivotTables across four dimensions, PivotCharts on retail and bike sales data |
| SQL-report | Databases & PostgreSQL | ERD design, all six join types, retail schema with a resolved many-to-many, ~20 queries including correlated subqueries — and fault-finding on deliberately broken SQL |
| Tableau-report | Tableau dashboards | Two published dashboards on global health and Spotify audio features — Top N filters, dashboard-level filtering, Percentage-of-Total table calculations |
| Power-BI-report | Power BI | Power Query transformation, a seven-table semantic model, DAX measures, slicers and hierarchy drill-down, published to Power BI Service (PL-300 and DP-900 labs) |
| Azure-report | Azure data fundamentals | Five DP-900 labs — Azure SQL Database, Storage, Cosmos DB, Microsoft Fabric — plus a cloud migration proposal covering UK GDPR, DPA 2018 and PCI DSS |
| Python-report | Python & pandas | Full pandas workflow, pd.cut grade banding, matplotlib and seaborn visualisation — including a documented bug where astype(str) turned missing values into a "nan" category |
Each repository carries the working files and screenshots, not just a description.
Data & analysis
Excel · SQL (PostgreSQL) · Python (pandas, NumPy) · data cleaning & validation · qualitative & quantitative analysis
Visualisation
Tableau · Power BI (DAX, Power Query) · matplotlib · seaborn · PivotTables & PivotCharts
Cloud & platforms
Azure SQL Database · Azure Blob Storage · Cosmos DB · Microsoft Fabric · Supabase · Google Colab
Governance
UK GDPR · Data Protection Act 2018 · Computer Misuse Act 1990 · PCI DSS awareness
Finance systems
Xero · Sage 50 · bank reconciliation · invoice processing · payroll support
Finance & Administration Assistant — CHAPS UK Ltd (2023–2024) Processed invoices, supported payroll and completed bank reconciliations across Excel, Xero and Sage 50. Identified discrepancies in financial records and kept documentation audit-ready under competing deadlines.
Warehouse Operative — temporary contracts (2020–present) Stock control and inventory documentation in target-driven environments. Flagged shortages and mismatches promptly to keep records accurate.
Independent Personal Trainer — part-time, self-employed (2024–present) Built a client base independently, tracked progress against goals and managed self-employment responsibilities end to end.
- Level 3 Data Technician Bootcamp — LeepTalent (2026, in progress)
- AAT Level 3 Diploma in Accounting (completed)
- AAT Level 2 Certificate in Accounting (completed)
- Business Foundation Programme — Birkbeck, University of London (completed)
- Business and Management, Year 1 — Kingston University
Seeking an entry-level Data Analyst, Data Technician, Junior Reporting Analyst or Finance Data Assistant role.
- Available from August 2026 · no sponsorship required · permanent right to work in the UK
- Open to relocating to London
- Bilingual — native Korean, professional working English
Next on the list: deepening SQL beyond single-table queries, and moving Python work from notebooks into reusable scripts.