Hana A.

I combine technical fluency (Python, SQL, GIS) with product and business strategy. GIS technician and programmer. Project manager. Expert in special tax and bond financial analysis. Bachelors in Computer Science (double major in Business Admin). With 7+ years of experience in data engineering, geospatial analytics, and compliance automation, I design workflows that transform raw datasets into APIs, dashboards, and insights that drive business outcomes. I have helped real estate, finance, and climate tech companies turn complex data into clean, usable, and profitable products. What I’ve Delivered: - Built scalable SQL + Python pipelines for real estate and insurance clients - Designed risk and tax models used in property underwriting and statutory disclosure products - Delivered 80% faster data turnaround through automation and workflow optimization - Integration of bonded-district data into enterprise SaaS and client APIs Technical Skills: - Languages & Tools: Python, SQL, Bash, pyodbc, pandas, NumPy, GDAL, WordPress, C, C++, HTML, VS, data scraping, Excel - Cloud: AWS, APIs - GIS & Mapping: ArcGIS, QGIS, Mapbox - Data Formats: CSV, JSON, XML - Workflows: Jira, Monday, Confluence, Teams, Slack - Industries I've Worked In: PropTech, FinTech, InsurTech, ClimateTech Core Services: - I design and automate data pipelines that bring clarity to complex, multi-source datasets. - ETL pipelines using Python (pandas, pyodbc, GDAL) - SQL data validation, schema design, QA/QC - Cloud data migration (AWS) - Workflow automation that cuts manual reporting time by 70–80% Whether you need recurring data processing or end-to-end infrastructure design, I help you get clean, consistent, and analytics-ready data. GIS & Risk Data Analysis: - Spatial analysis & visualization (ArcGIS, QGIS) - Risk modeling (wildfire, flood, seismic) - Python + SQL automation for geospatial workflows - Metadata, documentation, and reporting for compliance Other Skills: - Bond analysis and bond calculations/valuations - Data aggregation and analysis I bridge the gap between data engineering and business outcomes; combining the mindset of a product strategist with the precision of a data engineer.