Jasmin Joseph

A fully automated data pipeline for processing and analyzing global earthquake events. The project includes:

• Ingestion: Idempotent loading from USGS API with raw JSON preservation
• Transformation: dbt models with data quality tests (staging → marts)
• Orchestration: Apache Airflow with configurable backfills
• REST API: FastAPI service with circuit breaker, exponential backoff, and Prometheus metrics
• Visualization: Apache Superset dashboards with geospatial and statistical insights
• Storage: PostgreSQL with schema separation and connection pooling

Demonstrates end-to-end data engineering and backend development with a focus on reliability and observability.

A modern PostgreSQL-based data warehouse designed to support scalable analytics and reporting. This project demonstrates end-to-end data engineering practices, including:

• Data modeling & schema design using the Medallion (Bronze–Silver–Gold) architecture.
• ETL pipelines to extract, transform, and load raw transactional data.
• Data quality checks and validation for accuracy and reliability.
• Analytics-ready views for business intelligence and performance insights.
• Query optimization for efficient analysis at scale.

The project highlights best practices in data architecture, integration, and transformation, delivering clean, reliable datasets ready for business decision-making.

An interactive Tableau dashboard built to help HR managers analyze workforce data through both high-level summaries and detailed employee records.

• Summary View includes three analytical sections:
  • Overview: Displays total hires, active employees, and terminations; visualizes hiring and termination trends over the years; breaks down employees by department, job title, and location; and compares HQ vs. branch distributions.
  • Demographics: Highlights gender ratio, age groups, and education levels while exploring correlations between education and performance ratings.
  • Income Analysis: Examines salary comparisons by education and gender and analyzes how salary varies with age across departments.
• Employee Records View: Provides a comprehensive, filterable employee list (name, department, position, gender, age, education, salary) to enable detailed individual-level analysis.
• Designed with interactive filters and dynamic sections, empowering HR teams to quickly move from strategic insights to granular employee data for better decision-making.

A dual-dashboard visualization designed to analyze sales trends and customer performance through interactive KPIs and filters.

• The Sales Dashboard displays key metrics:Total Sales, Profit, and Quantity, along with sales and profit by subcategory and trend analyses over time, filterable by year.
• The Customer Dashboard highlights Total Customers, Sales per Customer, and Total Orders, supported by visuals showing customer distribution by order count and top customers by profit.
• Built with interactive navigation buttons to switch seamlessly between dashboards, enabling smooth exploration.
• Demonstrates advanced Tableau skills in dashboard linking, parameter control, and performance optimization for a business-ready visualization experience.