Joni Syofian

About Me

Data Engineer with experience in building ETL pipelines, writing optimized SQL queries, and ensuring data quality for business reporting. Strong in transforming raw data into actionable insights through dashboards and ad-hoc analysis. Experienced in collaborating with cross-functional teams to support business decision-making and improve data reliability.

Experience

Technical Consultant - PT IDX Consulting (March 2023 - Now)

Developed and optimized SQL queries to support ad-hoc business reporting and data analysis needs
Built and maintained ETL pipelines for large-scale data migration (Impala → Phoenix), improving data processing efficiency
Automated data processing using Python, reducing manual effort by 50%+
Monitored and validated data quality, identifying inconsistencies and performing root cause analysis (RCA)
Collaborated with business users and analysts to translate business requirements into data solutions
Supported creation of reporting datasets for dashboard and analytical use
Documented data flow, ETL mapping, and validation processes to ensure data integrity

Research Assistant - Bandung Institute of Technology (July 2022 - December 2022)

Collected, cleaned, and processed field data using Python and MATLAB for analysis and visualization
Transformed raw oceanographic datasets into structured data to support analytical workflows
Performed data analysis and visualization to generate insights on environmental and coastal data
Contributed to a published scientific book through data interpretation and technical documentation
Collaborated with research teams to ensure data accuracy, consistency, and reliable outputs

Projects

Data Pipeline Project

Built a production-style ETL pipeline using Python to process and transform raw data into clean, structured datasets. Ensured data quality through validation and logging, and utilized the output to design interactive Power BI dashboards, enabling clear visualization of sales performance and data-driven decision-making.

Python: ETL pipeline development (extract, validate, transform, load).
PostgreSQL: data storage and querying.
Power BI: dashboard and data visualization.

Data Science Bootcamp

These projects were created while taking part in a data science bootcamp series at Rakamin Academy and a virtual internship at ID/X Partners. The tools used are as follows:

Python : used for exploratory data analysis, data preprocessing, visualization, and machine learning.
SQL (PostgreSQL): used to create databases from csv files and perform queries on PostgreSQL.
Excel : used to perform simple visualizations.

Exploratory Data Analysis Dashboard

This project is a dashboard built using Streamlit. Users can upload data files in CSV or Excel format. The dashboard provides several analytical features, including:

Descriptive Statistics
Univariate Analysis
Bivariate Analysis
Multivariate Analysis

Cirebon Coastal Water Analysis Project

Contributed to oceanographic research by performing data collection, processing, and visualization of coastal water data using MATLAB. Analyzed nutrient and heavy metal distribution to generate insights, supporting a published scientific reference by ITB Press.

Tableau Public Dashboard Portfolio

Designed and published interactive data visualizations on Tableau Public, demonstrating skills in data analysis, storytelling, and dashboard development. Built dashboards to transform complex datasets into clear and actionable insights.

Data Enthusiast