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I will integrate all your data and engineer your data pipelines
Data Engineering, Pyspark, Azure, ETL Pipeline, SQL, Python
I am a qualified data engineer who bring 12 years of expertise into Data Engineering side which includes design and implement ETL (Extract, Transform, Load) processes to move data between systems. Mov...
About this Gig
Looking for a reliable and professional Data Engineer? Your search ends here!
With 13 years of experience in Data Engineering, I specialize in providing excellent ETL tailored to your specific needs. Whether you need ETL pipeline or need to process petabytes of data, I'm here to help you achieve your goals with personalized, high-quality solutions.
My Services Include:
- Data Cleaning and Tranformations using Spark.
- Building ETL pipeling using Pyspark or Azure Data Factory, Azure Databricks
- Data Migration from SQL Server to Azure Cloud (Delta).
Why Choose Me?
- Experience: With 12 years of experience, I bring in-depth knowledge and skills to your project.
- Quality: Committed to delivering work that exceeds your expectations.
- Communication: Keeping you updated and involved throughout the project
- Timeliness: Ensuring your project is completed on time.
How It Works?
- Initial Discussion: We'll talk about your requirements and goals.
- Planning: I'll develop a plan tailored to your needs.
- Execution: I will execute the plan with precision and care.
- Review: You'll review the work, and we'll make any necessary adjustments.
- Final Delivery: You'll receive the finished product, ready to use.
My Portfolio
FAQ
What’s the difference between a data pipeline and ETL?
A data pipeline is an automated system that transports data from source to destination. ETL (Extract, Transform, Load) refers to the process of extracting raw data, transforming it (cleaning and organizing), and loading it into a database or data warehouse.
Can you work with my existing data infrastructure?
Absolutely! I can work with your current tools and technologies (whether it's a SQL database, NoSQL system, or cloud service) and optimize the data workflows.
Will I be able to access the data in real-time?
Yes! I can set up real-time data processing pipelines that will continuously update your data as it’s collected, making it available for immediate use.
How do I receive the data once the pipeline is built?
Once the pipeline is built, the data can be stored in cloud storage, databases, or exported into the format of your choice (CSV, JSON, SQL, etc.) for easy access and analysis.
How long will it take to build the data pipeline?
The timeline depends on the complexity of the project. The Basic Package will be completed within 5 days, while more advanced projects may take up to 10 days for complex, real-time systems.
