Net2Source Inc.
Python Developer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Python Developer with Data Engineering experience, offering a hybrid contract in Reading, PA. The position requires 10+ years in data engineering, expertise in Talend, PySpark, and AWS services, focusing on ETL/ELT workflows and data pipeline optimization.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
March 10, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Reading, PA
-
🧠 - Skills detailed
#Data Quality #Datasets #AWS S3 (Amazon Simple Storage Service) #S3 (Amazon Simple Storage Service) #AWS (Amazon Web Services) #Cloud #Storage #Big Data #Python #SQL (Structured Query Language) #PySpark #Scala #Data Lake #Data Pipeline #Talend #Spark SQL #Data Processing #Data Engineering #Lambda (AWS Lambda) #Athena #"ETL (Extract #Transform #Load)" #Spark (Apache Spark)
Role description
Title- Python Developer with Data Engineering exp.
Location: Reading, PA (Hybrid)
The Team
You will be part of a high-performing Data Engineering & Analytics team responsible for building scalable, cloud-native data platforms on AWS. The team partners closely with product, analytics, and business stakeholders to deliver reliable data pipelines that support advanced analytics, reporting, and data-driven decision-making.
This team emphasizes modern data engineering practices, reusable frameworks, performance optimization, and production-grade data solutions.
The Role
As a Senior Data Engineer, you will design, build, and maintain end-to-end data pipelines leveraging Talend Cloud (8.0), PySpark, and AWS services. You will play a key role in ingesting, transforming, and optimizing large-scale structured and unstructured datasets while ensuring scalability, performance, and data quality across the platform.
Key responsibilities include:
• Designing and developing ETL/ELT workflows using Talend 8.0 on Cloud
• Integrating data from APIs, flat files, and streaming sources
• Ingesting and managing data in AWS S3–based data lakes
• Developing PySpark jobs for large-scale data processing and transformations
• Implementing Spark SQL for complex transformations and schema management
• Building and supporting cloud-native data pipelines using AWS services such as Glue, Lambda, Athena, and EMR
• Applying performance tuning and optimization techniques for Spark workloads
What You Will Bring
• 10+ years of experience in data engineering, big data, or ETL development roles
• Strong hands-on expertise with Talend ETL (Talend Cloud / Talend 8.x)
• Advanced experience in PySpark and Spark SQL for large-scale data processing
• Proficiency in Python, including building reusable data transformation modules
• Solid experience with AWS data services, including:
• S3 for data lake storage and lifecycle management
• Glue for ETL/ELT orchestration
• Lambda for event-driven processing
• Athena for serverless analytics
• EMR for Spark/PySpark workloads
• Strong understanding of ETL/ELT patterns, data lakes, and distributed systems
• Ability to optimize performance, ensure data quality, and build production-ready pipelines
• Excellent collaboration skills and experience working with cross-functional teams
Title- Python Developer with Data Engineering exp.
Location: Reading, PA (Hybrid)
The Team
You will be part of a high-performing Data Engineering & Analytics team responsible for building scalable, cloud-native data platforms on AWS. The team partners closely with product, analytics, and business stakeholders to deliver reliable data pipelines that support advanced analytics, reporting, and data-driven decision-making.
This team emphasizes modern data engineering practices, reusable frameworks, performance optimization, and production-grade data solutions.
The Role
As a Senior Data Engineer, you will design, build, and maintain end-to-end data pipelines leveraging Talend Cloud (8.0), PySpark, and AWS services. You will play a key role in ingesting, transforming, and optimizing large-scale structured and unstructured datasets while ensuring scalability, performance, and data quality across the platform.
Key responsibilities include:
• Designing and developing ETL/ELT workflows using Talend 8.0 on Cloud
• Integrating data from APIs, flat files, and streaming sources
• Ingesting and managing data in AWS S3–based data lakes
• Developing PySpark jobs for large-scale data processing and transformations
• Implementing Spark SQL for complex transformations and schema management
• Building and supporting cloud-native data pipelines using AWS services such as Glue, Lambda, Athena, and EMR
• Applying performance tuning and optimization techniques for Spark workloads
What You Will Bring
• 10+ years of experience in data engineering, big data, or ETL development roles
• Strong hands-on expertise with Talend ETL (Talend Cloud / Talend 8.x)
• Advanced experience in PySpark and Spark SQL for large-scale data processing
• Proficiency in Python, including building reusable data transformation modules
• Solid experience with AWS data services, including:
• S3 for data lake storage and lifecycle management
• Glue for ETL/ELT orchestration
• Lambda for event-driven processing
• Athena for serverless analytics
• EMR for Spark/PySpark workloads
• Strong understanding of ETL/ELT patterns, data lakes, and distributed systems
• Ability to optimize performance, ensure data quality, and build production-ready pipelines
• Excellent collaboration skills and experience working with cross-functional teams
