HELLO, I’M

Bodin Krongchon

Data Engineer building reliable, maintainable, and production-minded data pipelines.

I build data engineering systems using Python, SQL, ETL and ELT pipelines, data-quality checks, incremental loading, governance, lineage, monitoring, automated testing, Docker, CI/CD, privacy, and Git-based workflows.

View My Work → View GitHub

Open to Data Engineer opportunities

3 Completed Projects

pipeline = {
  "extract": true,
  "transform": true,
  "load": true,
  "quality_check": true,
  "lineage": true,
  "ci": true
}

CORE TECHNOLOGIES

Python

SQL

Pandas

SQLite

Docker

GitHub

ABOUT ME

Building dependable data systems

I focus on transforming raw business data into trustworthy, structured, secure, and reusable datasets for analytics, reporting, and operational decisions.

Production-minded engineering

My projects go beyond basic analysis. They include ingestion, transformation, incremental processing, validation, rejected-record handling, data quality, monitoring, lineage, governance, performance tuning, automated tests, Docker validation, CI/CD, privacy protection, and portfolio-safe outputs.

Reliable Validation, recovery, and quality gates

Observable Audit logs, SLA metrics, and lineage

Reproducible Fresh DB tests, Docker, and CI

3 Completed Projects

71 Tests in Project 03

SQL Modeling and Performance

CI GitHub Actions Validation

TECHNICAL SKILLS

Tools and engineering concepts

Current skills are technologies and engineering practices demonstrated in completed projects. Roadmap tools remain clearly separated from completed project experience.

Current project experience Planned project roadmap

CURRENT SKILLS

Programming

Python

Pandas

CLI

CURRENT SKILLS

Database and SQL

SQL

SQLite

FK Relational Design

IDX Indexing

QP Query Plans

V Analytical Views

ETL

CURRENT SKILLS

Data Engineering

ETL ETL

ELT ELT

Δ Incremental Load

DQ Data Quality

F Freshness

R Recovery / Backfill

G Governance

L Lineage

SLA Monitoring

CURRENT SKILLS

Engineering Practices

Git

GitHub

Docker

CI GitHub Actions

Testing

P Privacy

OBS Observability

PERF Performance

DOC Documentation

PROJECT ROADMAP

Database Expansion

PostgreSQL

MySQL

MongoDB

Linux

PROJECT ROADMAP

Automation and Modeling

Airflow

dbt

Terraform

PROJECT ROADMAP

Cloud Data Platform

Google Cloud

BQ BigQuery

AWS

S3 Cloud Storage

PROJECT ROADMAP

Big Data and Streaming

Apache Spark

Kafka

Hadoop

PS PySpark

COMPLETED PROJECTS

Featured data engineering work

View GitHub Profile →

Excel

→

Python

→

SQLite

PYTHON · SQL · ETL

E-commerce Data Pipeline

Multi-source ingestion, cleaning, transformation, validation, database loading, and portfolio reporting.

View Repository ↗

RAW Raw

→

DQ Validate

→

SAFE Masked

QUALITY · PRIVACY · TESTING

Marketing Campaign Data Platform

Payment-data validation, rejected records, audit reporting, sensitive-data masking, and automated tests.

View Repository ↗

DB Pipeline

→

DQ Govern

→

CI Validate

SQL · RELIABILITY · GOVERNANCE

SQL E-commerce Data Engineering

Production-style SQL data platform with 22 tables, 19 views, 49 indexes, incremental loading, freshness and quality gates, recovery/backfill, governance and lineage, performance tuning, Docker, GitHub Actions CI, and 71 automated tests.

View Repository ↗

3 Projects Completed

71 Automated Tests in Project 03

1 Verified Certificate

100% Data Engineering Focus

CERTIFICATE

Verified learning and professional development

CERTIFICATE OF COMPLETION The School of Generalist Data Science Bootcamp Batch 12

ID: bd4399be-11a9-4f29-9cb6-4c5762414fc3

DATAROCKIE

Data Science Bootcamp Batch 12

A multidisciplinary program covering SQL, Python, statistics, essential machine learning, dashboards, web fundamentals, analytical thinking, and artificial intelligence.

Issue Date 29 April 2026

Provider DataRockie

SQL

Python

ST Statistics

ML Machine Learning

BI Dashboard

AI AI

View Verified Certificate ↗

NEXT PROJECT MILESTONES

Data Engineering learning roadmap

These technologies are planned for upcoming projects and are not presented as completed production experience.

PROJECT 04 · AUTOMATION

Apache Airflow

DAGs, scheduling, retries, backfills, monitoring, alerting, and pipeline auditing.

PROJECT 05 · ANALYTICS ENGINEERING

dbt

Modular SQL models, testing, documentation, lineage, staging models, and data marts.

PROJECT 06 · CLOUD DATA

Google Cloud

Cloud Storage, BigQuery, partitioning, cloud pipelines, access control, and cost awareness.

PROJECT 07 · BIG DATA

PySpark

Distributed processing, partitioned data, large-scale transformations, and performance optimization.

PROJECT 08 · STREAMING

Apache Kafka

Event producers, consumers, topics, streaming ingestion, delivery guarantees, and monitoring.

PROJECT FOUNDATION · INFRASTRUCTURE

Linux and Infrastructure

Linux command-line workflows, filesystems, services, networking, permissions, and environment configuration.

LET’S WORK TOGETHER

Let’s build reliable data systems.

I am open to Data Engineer opportunities, professional connections, and project discussions.

Send Email →

Email bodin.kc30@gmail.com ↗ Phone 063-885-5927 ↗ GitHub bodinkc30-Pete ↗ LinkedIn Bodin Krongchon ↗