I will build, fix and optimize etl pipelines using azure databricks
Azure Databricks Engineer, ETL Pipelines, PySpark, Delta Lake
About this Gig
Are you facing issues with slow, failing, or inefficient ETL pipelines in Azure Databricks?
I help businesses build, fix, and optimize data pipelines using Databricks and PySpark to ensure reliable, scalable, and high-performance workflows.
What I can do:
- Build ETL/ELT pipelines using Azure Databricks
- Process and transform large datasets with PySpark
- Debug and fix pipeline errors and failures
- Optimize Databricks jobs for performance and cost efficiency
- Implement Delta Lake, Lakehouse architecture, and Unity Catalog for data governance
Why choose me:
- Hands-on experience with real-world Databricks projects
- Strong understanding of ETL pipelines and performance optimization
- Focus on scalable and production-ready solutions
- Clear communication and quick turnaround
Feel free to message me before placing an order to discuss your requirements.
Destination Platform:
Snowflake
•
Databricks Lakehouse
Tools & Platforms:
Oracle GoldenGate
•
Azure Data Factory
My Portfolio
FAQ
What do you need to get started?
I need a brief description of your requirement, data source details, and access to your existing pipeline or environment if applicable.
Can you fix issues in my existing Databricks pipeline?
Yes, I can analyze, debug, and fix errors in existing Azure Databricks and PySpark pipelines, including performance issues.
Do you support performance optimization?
Yes, I can optimize Databricks jobs, queries, and pipelines to improve performance and reduce cost.
Can you work with large-scale data?
Yes, I have experience working with large datasets using PySpark and Databricks for scalable data processing.
Do you provide end-to-end pipeline solutions?
Yes, I can design and build complete ETL pipelines, including data ingestion, transformation, and storage using Delta Lake and Lakehouse architecture.

