Human-Capital-Data-Pipeline
Final project for Full-Stack Data Engineering program focusing on data pipeline implementation and analytics.
I build scalable data pipelines and engineer robust software solutions. Currently focused on data engineering and cloud infrastructure.
My name is Ricky Suhanry, people usually call me by the nickname "Rick". I was born in the capital city of Bangka Belitung, located on Bangka Belitung Island, Indonesia. I came from IT/software engineer background with a Bachelor of Informatics Engineering at Tarumanagara University. After being a Backend Engineer in the year 2023, I decided to transition into a data field. In July 2024, I enrolled in the Fast Track Data Engineer program as a full-time student in Digital Skola. Continue to next year in January 2025, I enrolled in the Data Engineering Cohort 2025 in Data Engineering Zoomcamp from Datatalksclub.
My experience as a data practitioner covers Engineering, Analytics, and Data Quality leveraging technical tools and platforms like Python, SQL, NoSQL, Apache Spark, Dbt, Airflow, Looker Studio, Metabase, Snowflake, and AWS/GCP. Although my core technical skill was Data Engineer, I also have had a keen interest in exploring more about DevOps, Machine Learning, and Generative AI. In my free time, I jog and running as a hobby, listening to Jpop music, and trying to learn the Japanese language.
Python
Java
TypeScript
SQL
Node.js
Express.js
Django
FastAPI
AWS
S3, Glue, RDS, Redshift
Google Cloud
BigQuery, GCS, Looker Studio
Databricks
Snowflake
HDFS
Apache Spark
Apache Airflow
Apache Kafka
Apache Flink
Apache Hive
Pandas
NumPy
dbt
Tableau
Metabase
Scikit-learn
Docker
Terraform
GitHub
GitLab
JIRA
AWS & Orbit Academy | July 2025 – Present
Hashnode | June 2025 – Present
Celerates | March 2025 – Jul 2025
DataTalksClub | January 2025 – April 2025
Final project for Full-Stack Data Engineering program focusing on data pipeline implementation and analytics.
Formula 1 Racing Team Alpha seeks to establish a comprehensive data pipeline to transform raw race data into actionable insights that improve race strategy, car performance, and driver development. Currently, the team struggles with siloed data systems, manual data processing, and delayed access to critical information during race weekends. Decision-making is often based on incomplete information or intuition rather than data-driven analysis.
Detail analysis of sales and profit from SuperStore dataset focusing on country, region, category, and sub-category from product variable.