I will build you a data pipeline using python databricks and AWS
About this Gig
Are you looking for a reliable Data Engineer to build scalable, production-ready data pipelines?
I am a 2025 B.Tech CS graduate specializing in Data Engineering with hands-on experience building end-to-end pipelines using Python, SQL, Apache Airflow, AWS, Databricks and dbt.
What I can build for you:
- ETL pipelines that extract, transform and load data from any source
- Bronze-Silver-Gold medallion architecture pipelines on Databricks or AWS
- Automated pipelines with Apache Airflow orchestration
- Data quality checks and validation frameworks
- dbt transformation models with full lineage documentation
My tech stack:
Python | SQL | Apache Airflow | AWS (S3, Glue, Lambda, Athena) | Databricks | Delta Lake | dbt | Snowflake | PySpark | Docker
Why choose me:
- Real project experience not just theory
- Clean, well-documented code
- Fast delivery at competitive prices
- Open to revisions until you are satisfied
Whether you need a simple ETL pipeline or a full production-grade data platform, I am here to help.
Let's build something great together!
Tools & Platforms:
AWS Glue DataBrew
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Other
FAQ
What information do you need to start the project?
I need details about your data source (API, CSV, database), target destination, and any specific transformation requirements. The more details you provide, the better I can deliver.
Which tools and technologies do you use?
I work with Python, SQL, Apache Airflow, AWS (S3, Glue, Lambda, Athena), Databricks, Delta Lake, dbt, Snowflake and PySpark.
Will you provide documentation with the pipeline?
Yes, all packages include documentation covering the pipeline architecture, setup instructions and how to run it.
Can you work with my existing data infrastructure?
Yes, I can adapt to your existing setup. Just share the details and I will build accordingly.
What if I am not satisfied with the delivery?
I offer revisions based on your package. I will work with you until you are satisfied with the final result.

