Scalable Data Pipeline for Clean and Reliable InsightsHatim Belfarhounia
I offer full-service data engineering services that turn raw, messy data into clear, organized, and useful information. I make sure that the results are fast, reliable, and scalable, and that they meet the needs of your business by using automated pipelines, modern tools, and best practices. What makes my work stand out is that I focus on being efficient, accurate, and fully documenting everything.
What's included
Cleaned & Structured Dataset
- A fully processed dataset with accurate, consistent, and well-formatted data.
- Delivered in CSV, Parquet, or Excel format.
- Includes up to 2 revisions based on client feedback.
Data Pipeline Scripts
- Python scripts or Jupyter notebooks automating data extraction, cleaning, and transformation.
- Includes documentation for setup and execution.
- Delivered in .py or .ipynb format.
Project Report and Insights
- Summary report detailing data sources, cleaning steps, and key findings.
- Recommendations for further analysis or optimization.
- Delivered in PDF or Word format.
Deployment Guide / Automation Setup
- Instructions for deploying the pipeline on local or cloud environments (AWS, GCP).
- Includes environment setup, dependencies, and scheduling guidance.
FAQs
I deal with unstructured, semi-structured, and structured data from databases, web scraping, CSV/Excel files, cloud storage, and APIs.
To guarantee dependable and consistent results, I use automated cleaning, validation, and transformation processes in addition to extensive testing.
AWS/GCP services, Python, Pandas, PySpark, Airflow, PostgreSQL, and contemporary ETL frameworks that are adapted to the efficiency and scalability requirements of projects.
Yes, I design pipelines to run on schedules or triggers, ensuring real-time or periodic data updates with minimal manual intervention.
Absolutely. Every project comes with detailed documentation, setup instructions, and support for revisions or troubleshooting.
Depending on size and complexity, standard datasets are typically delivered in 3–5 business days with clear communication at every stage.
Contact for pricing
Tags
Apache Spark
Docker
PostgreSQL
Python
Data Analyst
Database Specialist
Database Engineer
Service provided by
Hatim Belfarhounia Casablanca, Morocco
- 6
- Followers
Scalable Data Pipeline for Clean and Reliable InsightsHatim Belfarhounia
Contact for pricing
Tags
Apache Spark
Docker
PostgreSQL
Python
Data Analyst
Database Specialist
Database Engineer
I offer full-service data engineering services that turn raw, messy data into clear, organized, and useful information. I make sure that the results are fast, reliable, and scalable, and that they meet the needs of your business by using automated pipelines, modern tools, and best practices. What makes my work stand out is that I focus on being efficient, accurate, and fully documenting everything.
What's included
Cleaned & Structured Dataset
- A fully processed dataset with accurate, consistent, and well-formatted data.
- Delivered in CSV, Parquet, or Excel format.
- Includes up to 2 revisions based on client feedback.
Data Pipeline Scripts
- Python scripts or Jupyter notebooks automating data extraction, cleaning, and transformation.
- Includes documentation for setup and execution.
- Delivered in .py or .ipynb format.
Project Report and Insights
- Summary report detailing data sources, cleaning steps, and key findings.
- Recommendations for further analysis or optimization.
- Delivered in PDF or Word format.
Deployment Guide / Automation Setup
- Instructions for deploying the pipeline on local or cloud environments (AWS, GCP).
- Includes environment setup, dependencies, and scheduling guidance.
FAQs
I deal with unstructured, semi-structured, and structured data from databases, web scraping, CSV/Excel files, cloud storage, and APIs.
To guarantee dependable and consistent results, I use automated cleaning, validation, and transformation processes in addition to extensive testing.
AWS/GCP services, Python, Pandas, PySpark, Airflow, PostgreSQL, and contemporary ETL frameworks that are adapted to the efficiency and scalability requirements of projects.
Yes, I design pipelines to run on schedules or triggers, ensuring real-time or periodic data updates with minimal manual intervention.
Absolutely. Every project comes with detailed documentation, setup instructions, and support for revisions or troubleshooting.
Depending on size and complexity, standard datasets are typically delivered in 3–5 business days with clear communication at every stage.
Contact for pricing