You will get data engineering projects using python, sql, spark, airflow, aws, azure gcp
Project details
This project involves designing and implementing comprehensive data engineering solutions utilizing Python, SQL, Apache Spark, and Apache Airflow across AWS, Azure, and GCP. The focus is on creating robust ETL pipelines to automate data ingestion from diverse sources, transform raw data into structured formats, and load it into optimized cloud data warehouses like AWS Redshift, Azure Synapse Analytics, and GCP BigQuery. By orchestrating workflows with Apache Airflow, the project ensures efficient task scheduling, monitoring, and error handling, while employing cloud storage solutions for scalable data management. The outcome is improved data processing efficiency, enhanced data quality, and timely access to critical insights for analytics and reporting, enabling data-driven decision-making for stakeholders.
Database Type
MySQL, MS SQL, MS Access, Oracle, SQLite, PostgreSQL, MongoDB, Azure Cosmos DBWhat's included
| Service Tiers |
Starter
$30
|
Standard
$60
|
Advanced
$120
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 5 days |
Number of Revisions | 1 | 2 | 3 |
Number of Queries | 3 | 5 | 7 |
Query Debugging | |||
Query Optimization | - | - | |
Query Scheduling | - | ||
Query Analysis | |||
Source Code |
About Aumit
Data Engineer/Analyst/Scientist | Python, SQL, Spark
Gazipur, Bangladesh - 4:12 pm local time
Expert in Python, SQL, R, ETL/ELT, Apache Spark, dbt, Databricks, Snowflake, real-time pipelines, and full cloud platforms (AWS, Azure, GCP). I also specialize in Power BI, Tableau, Salesforce Data Cloud & Agentforce for unified analytics and intelligent AI agents.
What I deliver:
* End-to-end data pipelines & modern data warehouses (Spark + dbt transformations)
* Production-ready Machine Learning & AI model pipelines
* Interactive dashboards that drive business decisions
* Data migration, optimization & automation from Excel/Google Sheets to enterprise scale
Clean, well-documented, maintainable solutions delivered fast in the AI era.
Ready to turn your raw data into a competitive advantage. Let’s discuss your project!
Steps for completing your project
After purchasing the project, send requirements so Aumit can start the project.
Delivery time starts when Aumit receives requirements from you.
Aumit works on your project following the steps below.
Revisions may occur after the delivery date.
Project Planning
Define goals, requirements, and data sources for the project.
Environment Setup
Configure cloud services and establish the development environment.