Amoa Appiah Daniella

I’m a Data Engineer and Data Analyst with a strong foundation in database technology, ETL pipeline development, and analytical reporting. I design production-grade data models, write complex SQL, and build Python-based pipelines that move data from raw sources into actionable insights.

In my TikTok Live Analytics Platform, I designed a multi-source ETL pipeline using an adapter pattern to unify TikTokLive, Live Center API, and mock data into one interface. I modelled a normalized PostgreSQL schema, implemented idempotent re-runs to prevent duplication, and delivered dual outputs to PostgreSQL and BigQuery alongside KPI dashboards for retention, engagement rate, gift revenue, and chat moderation flags.

I also turn data into clear, decision-ready narratives—querying PostgreSQL for stream engagement analysis and using Matplotlib/Seaborn visualizations to identify peak engagement windows and patterns tied to gift revenue and chat interaction. Through projects like Equilens (a React/Next.js compliance dashboard) and the World Bank labour market analysis, I’ve built audit-ready reporting views and produced styled workbooks and presentations from cleaned WDI datasets.

Most recently, as a Software Intern at Wise Robotics, I collaborated with engineers to automate data collection workflows, optimize relational database schemas with SQL, and analyze operational data using SQL and Python (Pandas) to surface trends and anomalies. I’m currently pursuing a structured 10-month data engineering and analytics roadmap, and I’m eager to contribute to teams that value robust data infrastructure and data-driven decision making.