I will build etl pipelines using python, sql and cloud platforms
Data Engineer
Sobre este Serviço
Are you looking for a reliable Data Engineer to build scalable ETL/ELT pipelines, automate workflows, and transform raw data into analytics-ready datasets?
I can help you design and develop modern data engineering solutions using Python, SQL, cloud platforms, and big data technologies.
Services I Offer
- ETL / ELT pipeline development
- Data extraction from APIs, databases, CSV, Excel, and cloud storage
- SQL query writing and optimization
- PySpark and Databricks transformations
- dbt data modeling
- Data warehouse and lakehouse solutions
- Azure, AWS, and GCP data pipelines
- Data cleaning and automation
- Batch and real-time data processing
- BI-ready datasets for Power BI or Looker Studio
Technologies
Python, SQL, PySpark, Databricks, dbt, Azure Data Factory, Synapse, AWS Glue, Athena, BigQuery, Snowflake, Kafka, Power BI, and more.
Why Choose Me?
- Scalable and clean solutions
- Cloud-native architecture
- Fast communication and support
- Well-structured and documented pipelines
- Focus on performance and reliability
Please contact me before placing an order so I can understand your requirements and recommend the best solution for your project.
Warehouse Platform:
Snowflake
•
BigQuery
•
Databricks
Tipo de projeto:
New Build
Meu portfólio
Perguntas frequentes
What technologies do you work with?
I work with Python, SQL, PySpark, Databricks, dbt, Azure, AWS, GCP, BigQuery, Snowflake and Synapse.
Can you build cloud-based ETL pipelines?
Yes, I can build scalable ETL/ELT pipelines on Azure, AWS, and GCP using modern cloud-native tools.
Do you work with APIs and automation?
Yes, I can extract data from APIs, automate workflows, and integrate data into warehouses, dashboards, or reporting systems.
Can you optimize existing SQL queries or pipelines?
Yes, I can optimize SQL queries, improve ETL performance, and redesign inefficient data workflows.
What do you need from me before starting?
Clear project requirements, source details, expected output, sample data (if available), and platform access if required. I prefer clarity.

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