Technical Skills
- Languages: Python, C/C++, SQL, R
- Databases: MySQL, PostgreSQL, SQL Server, MongoDB
- Data Tools: Spark, Pandas, dbt, Nifi, dlt
- Visualization: Power BI, Streamlit, Metabase
- Orchestration: Dagster, Airflow, MLflow
- Delivery: Docker, Git
Data Engineering · DataOps
I am Haiden, based in Ho Chi Minh City. I build resilient data pipelines, production-grade workflows, and analytics products that turn complex signals into confident decisions.
I specialize in data engineering and operational excellence, blending robust architecture with practical delivery. My work spans ingestion, transformation, orchestration, and deployment with a clear focus on stability and measurable impact.
Navigate key roles and measurable outcomes across my recent internships.
Designed a scalable real-time ingestion framework with Apache NiFi and N8N for IoT streams, cutting pipeline latency by 50%.
Built transformation and loading flows into MongoDB, then published processed data to MQTT for real-time insight delivery.
Developed and deployed forecasting models (Prophet, LightGBM) through MLflow, reaching 10% MAPE.
Redesigned daily Claim Report reset pipelines on Microsoft Fabric and reduced runtime by 30%.
Rebuilt a dynamic renewal reporting layer in Power BI to improve exposure, renewal-rate, and premium visibility across territories.
Performed data cleaning, modeling, transformation, and statistical analysis to support actuarial decisions.
A clear path from hands-on engineering delivery to leading data platform strategy.
Build strong expertise as a data engineer focused on scalable data platform foundations and reliable delivery.
Grow into senior-level ownership while expanding into product planning and roadmap execution as PM/PO.
Lead teams and architecture direction, translating business goals into end-to-end platform and solution strategy.
Scalable pipelines, robust ETL, and resilient architectures that keep data trustworthy and available.
Automated workflows, orchestration, and CI/CD for data systems that ship faster with fewer incidents.
Applied modeling and analytics that transform raw operational data into clear business outcomes.
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Developed an end-to-end football analytics pipeline with Dockerized services for extraction, transformation, and dashboard delivery through Streamlit.
Stack: Python, Docker, ETL, Streamlit
Open Repository