Fadli Insani

Data Engineer with 2 years of experience designing, automating, and maintaining end-to-end ETL/ELT data pipelines using Python and SQL to deliver reliable, analysis-ready data. Experienced in building end-to-end data ecosystems—from multi-source ingestion and data modeling to data quality validation and accessibility—ensuring consistent metrics across teams. Skilled in building interactive self-service dashboards with Streamlit and Chart.js to translate raw data into decisions that drive business impact.

Data Analyst and Data Engineering - Staff at PT.

Migunani Langgeng

Jati (2024-11 – Present)

• End-to-End Pipeline Automation: Integrated data from multiple sources (databases, APIs, spreadsheets) into a centralized data warehouse and automated ETL/ELT ingestion and transformation workflows, eliminating manual data preparation.
• Data Quality & Pipeline Reliability: Implemented automated data quality checks and validation rules to catch anomalies before reaching production reports, while scheduling and monitoring pipelines with real-time alerting for failures and delays.
• Query & Model Optimization: Optimized SQL queries and relational data models to improve execution performance and significantly reduce data processing time.
• Data Governance & Documentation: Standardized metric definitions across departments to ensure single-source-of-truth reporting and documented data flows, table definitions, and business logic for cross-team reusability.
• Business Intelligence & Requirements: Gathered requirements from stakeholders, translated business questions into actionable KPIs, and designed self-service dashboards with interactive drill-downs and filters.
• Stakeholder Enablement: Trained business users to interpret and navigate dashboards independently and iteratively refined dashboard layouts based on user feedback to maximize adoption.