Senior Data Engineer

Title- Senior Data Engineer Location- Reading, PA, 5 days onsite 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