You will get ETL/ELT pipelines using Azure Databricks and PySpark
Project details
Need a reliable Azure Databricks ETL pipeline for your business?
I will design, develop, and optimize scalable ETL and ELT pipelines using Azure Databricks, PySpark, Delta Lake, SQL, and Microsoft Fabric.
My services include:
• Data ingestion from APIs, databases, CSV, Excel, SFTP, and cloud storage
• Data transformation and cleansing using PySpark
• Delta Lake implementation and optimization
• Incremental loading and merge/upsert logic
• ETL and ELT pipeline development
• Data validation and quality checks
• Query optimization and performance tuning
• Data warehouse integration
• Analytics-ready data preparation
Why work with me?
• Hands-on experience with Azure Databricks and modern Lakehouse architectures
• Strong expertise in PySpark, SQL, Delta Lake, and Microsoft Fabric
• Production-ready, scalable, and maintainable solutions
• Clean code, documentation, and ongoing support
Whether you need a new ETL pipeline, data migration, or performance optimization, I can help deliver a reliable and scalable data engineering solution.
I will design, develop, and optimize scalable ETL and ELT pipelines using Azure Databricks, PySpark, Delta Lake, SQL, and Microsoft Fabric.
My services include:
• Data ingestion from APIs, databases, CSV, Excel, SFTP, and cloud storage
• Data transformation and cleansing using PySpark
• Delta Lake implementation and optimization
• Incremental loading and merge/upsert logic
• ETL and ELT pipeline development
• Data validation and quality checks
• Query optimization and performance tuning
• Data warehouse integration
• Analytics-ready data preparation
Why work with me?
• Hands-on experience with Azure Databricks and modern Lakehouse architectures
• Strong expertise in PySpark, SQL, Delta Lake, and Microsoft Fabric
• Production-ready, scalable, and maintainable solutions
• Clean code, documentation, and ongoing support
Whether you need a new ETL pipeline, data migration, or performance optimization, I can help deliver a reliable and scalable data engineering solution.
Database Type
MS SQL, PostgreSQL, Azure Cosmos DBWhat's included
| Service Tiers |
Starter
$25
|
Standard
$35
|
Advanced
$50
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 3 days |
Number of Revisions | 1 | 2 | 5 |
Number of Queries | 3 | 7 | 15 |
Query Debugging | |||
Query Optimization | - | ||
Query Scheduling | - | ||
Query Analysis | - | ||
Source Code | - |
Frequently asked questions
About Muhammad
Data Engineer | Databricks | PySpark | Microsoft Fabric | Snowflake
Faisalabad, Pakistan - 3:34 am local time
I have successfully delivered enterprise-grade data solutions across retail, manufacturing, marketing, finance, and customer analytics domains. My experience includes building Bronze-Silver-Gold lakehouse architectures, integrating complex APIs, automating ingestion frameworks, designing data warehouses, and optimizing large-scale distributed data workloads.
Key areas of expertise include:
✔ Azure Databricks & PySpark
✔ Microsoft Fabric (Lakehouse, Data Pipelines, Warehouse)
✔ Snowflake Data Warehousing
✔ Azure Data Factory (ADF)
✔ Delta Lake & Lakehouse Architecture
✔ ETL / ELT Pipeline Development
✔ Azure SQL & Data Modeling
✔ REST APIs, FastAPI & GraphQL Integrations
✔ Data Migration & Modernization Projects
✔ Data Quality, Validation & Monitoring
✔ Power BI & Analytics Enablement
Some of the solutions I have delivered include customer data platforms, enterprise data warehouses, marketing analytics systems, retail modernization projects, API-driven ingestion frameworks, and automated reporting ecosystems.
I focus on building reliable, scalable, and maintainable data solutions that help organizations transform raw data into actionable business insights.
Let's connect if you need a Data Engineer who can architect, build, and optimize modern cloud data platforms from end to end.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis
Review business requirements, data sources, existing architecture, and project objectives. Define the ETL strategy and implementation approach.
Pipeline Development
Develop ETL or ELT pipelines using Azure Databricks, PySpark, SQL, and Delta Lake. Implement required transformations and validations.