15+ Senior Backend Python Developer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a 15+ Senior Backend Python Developer on a contract basis, offering a competitive pay rate. Key skills include Python backend development, Databricks experience, and data engineering expertise. Strong knowledge of RESTful APIs and cloud integration is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 27, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
New York City Metropolitan Area
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🧠 - Skills detailed
#Deployment #Databricks #"ETL (Extract #Transform #Load)" #Swagger #Django #Spark (Apache Spark) #ADF (Azure Data Factory) #Cloud #Docker #Flask #Scala #SQL (Structured Query Language) #Data Pipeline #Storage #Python #Azure #Azure Data Factory #Data Quality #Security #Automation #Data Engineering #Documentation #SQLAlchemy #Data Lake #PySpark #Programming #API (Application Programming Interface) #Delta Lake #Distributed Computing #pydantic #NoSQL #Schema Design #FastAPI #Logging #Monitoring #Data Modeling #Pytest #Data Processing
Role description
Role Summary
Skills
Python Backend Development:
• Strong expertise in Python 3.x, with a focus on backend systems.
• Experience with Python web frameworks (FastAPI, Flask, Django, or similar).
• Data validation and serialization using Pydantic.
• ORM experience (SQLAlchemy, SQLModel, or similar).
• RESTful API design, implementation, documentation (OpenAPI/Swagger).
• Unit, integration, and end-to-end testing of APIs (pytest, unittest).
• Security best practices (authentication, authorization, API security).
• Asynchronous programming with Python (async/await, asyncio).
• Performance optimization, caching strategies, and error handling.
• Experience with Docker and containerized backend deployments.
Databricks & Data Engineering:
• Experience with Databricks for large-scale data processing and analytics.
• Proficient in writing and optimizing PySpark jobs/notebooks for ETL and data transformation.
• Strong understanding of distributed computing concepts.
• Working knowledge of data lake architectures and Delta Lake.
• Building scalable data pipelines using Azure Data Factory and Databricks.
• Automation of data quality checks, monitoring, and logging.
• Integration with cloud data sources (Azure Blob, Data Lake Storage, SQL/NoSQL DBs).
• Data modeling and schema design for analytical workloads.
• Experience with CI/CD for Databricks notebooks and jobs.
Knowledge of workspace administration, cluster management, and job orchestration in Databricks Thanks and Best Regards
Role Summary
Skills
Python Backend Development:
• Strong expertise in Python 3.x, with a focus on backend systems.
• Experience with Python web frameworks (FastAPI, Flask, Django, or similar).
• Data validation and serialization using Pydantic.
• ORM experience (SQLAlchemy, SQLModel, or similar).
• RESTful API design, implementation, documentation (OpenAPI/Swagger).
• Unit, integration, and end-to-end testing of APIs (pytest, unittest).
• Security best practices (authentication, authorization, API security).
• Asynchronous programming with Python (async/await, asyncio).
• Performance optimization, caching strategies, and error handling.
• Experience with Docker and containerized backend deployments.
Databricks & Data Engineering:
• Experience with Databricks for large-scale data processing and analytics.
• Proficient in writing and optimizing PySpark jobs/notebooks for ETL and data transformation.
• Strong understanding of distributed computing concepts.
• Working knowledge of data lake architectures and Delta Lake.
• Building scalable data pipelines using Azure Data Factory and Databricks.
• Automation of data quality checks, monitoring, and logging.
• Integration with cloud data sources (Azure Blob, Data Lake Storage, SQL/NoSQL DBs).
• Data modeling and schema design for analytical workloads.
• Experience with CI/CD for Databricks notebooks and jobs.
Knowledge of workspace administration, cluster management, and job orchestration in Databricks Thanks and Best Regards
