Open to Opportunities

Naveed
Ahmed Jokhio

Cloud Data Engineer

I am an aspiring Cloud Data Engineer with hands-on experience in designing ETL/ELT pipelines using AWS, Snowflake, and dbt. Skilled in building scalable data models and incremental processing for analytics-ready data warehouses.

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01 — About Me

Passionate about Data

I am Naveed Ahmed Jokhio, an aspiring Cloud Data Engineer passionate about building robust, scalable data infrastructure that powers real business decisions. I specialize in designing and implementing ETL/ELT pipelines using AWS, Snowflake, and dbt.

I've gained hands-on internship experience at Arch Technologies (current) and HexSoftwares — working on real-world datasets, performing data cleaning, exploratory analysis, and building data workflows using Python. These experiences deepened my understanding of how clean, well-modeled data drives analytics.

My core stack includes Python, SQL, Pandas, NumPy, AWS (S3, Glue, Lambda), Snowflake, and dbt. I'm continuously sharpening my skills in pipeline orchestration with Apache Airflow and cloud-native data architectures. My goal is to engineer reliable data systems that turn raw, messy data into analytics-ready value.

AWS

S3 · Glue · Lambda

dbt

Transformations

Snowflake

Data Warehousing

02 — Skills

Technical Stack

🐍 Languages & Libraries

Python82%

SQL78%

Pandas / NumPy80%

Seaborn / Matplotlib72%

☁️ Cloud & Warehouse

AWS (S3, Lambda, Glue)62%

Snowflake55%

ETL / ELT Pipelines68%

Apache Airflow48%

🗄️ Databases & Tools

PostgreSQL / MySQL75%

Data Modeling65%

Git / GitHub82%

dbt42%

03 — Projects

Featured Work

Airbnb End-to-End Data Engineering

Production-style Cloud Data Platform — S3 → Snowflake → dbt with Medallion Architecture.

🥉 Bronze — Raw S3 ingestion, incremental loading.
🥈 Silver — Cleaning, deduplication, incremental upserts.
🥇 Gold — Star Schema, SCD Type-2, One Big Table.

AWS S3 Snowflake dbt Python SQL Medallion Arch Star Schema SCD Type-2

View on GitHub →

AWS Serverless ETL Pipeline

End-to-end serverless ETL pipeline — JSON data ingested via S3, processed with AWS Lambda, flattened to Parquet (Data Lake), catalogued with Glue & analysed using Athena. Fully event-driven, zero server management.

AWS S3 Lambda Glue Athena Python Parquet Serverless ETL

04 — Experience

Work Experience

💼

Data Science Intern

Arch Technologies

📅 Jan 2026 – Mar 1, 2026 · 2 Months · Remote

Worked on data science tasks — performed data analysis, data cleaning, and applied Python to extract meaningful insights from real-world datasets. Gained hands-on experience with data loading workflows and analytical pipelines.

Python Data Analysis Data Cleaning Data Loading

📊

Data Science Intern

HexSoftwares

📅 Jan 2026 – Jan 2026 · 1 Month · Remote

Worked on real-world datasets as part of a data science internship — performed data cleaning, exploratory data analysis (EDA), and extracted actionable insights using Python and Pandas.

Python Pandas EDA Data Cleaning Data Science

05 — Education