ETL Data Engineer With Telecom Domain_ (West Chester, PA _Onsite _Need local _No Relocation _F2F Interview)

Job Title:

Telecom ETL Data Engineer Location:

West Chester, PA Job Description We are seeking an experienced Telecom ETL Data Engineer with strong expertise in big data technologies, PySpark, and Databricks to design, develop, and optimize scalable ETL pipelines for telecom data platforms. The ideal candidate will have hands-on experience working with large-scale telecom datasets, real-time data processing, and cloud-based analytics solutions. Key Responsibilities Design, develop, and maintain scalable ETL/data pipelines using PySpark and Spark SQL. Build and optimize data workflows in Databricks including Delta Lake, Jobs, and Clusters. Develop modular and reusable Python-based ETL frameworks. Process and analyze large telecom datasets from operational and business systems. Implement batch and streaming data solutions using Spark Streaming and Kafka where applicable. Collaborate with cross-functional teams including business stakeholders, architects, and analysts. Perform Spark performance tuning and optimization for high-volume data workloads. Integrate CI/CD pipelines and maintain version control using Git. Work with orchestration tools such as Airflow, Rundeck, or Control-M for workflow automation. Support cloud-native implementations across Azure, AWS, or Google Cloud Platform environments. Translate complex technical concepts into business-friendly insights and presentations. Technical Skills Strong hands-on experience with PySpark, Spark SQL, and Spark Streaming . Proven expertise in Databricks (Delta Lake, Jobs, Clusters). Strong Python programming and ETL development experience. Experience working with telecom systems, operational workflows, and telecom data domains. Knowledge of CI/CD processes, Git, and cloud platforms (Azure/AWS/Google Cloud Platform). Experience with workflow orchestration tools such as Airflow, Rundeck, or Control-M. Preferred Qualifications Experience working with telecom providers such as Comcast/Xfinity, AT&T, Verizon, or similar. Knowledge of event-driven architecture and real-time streaming technologies like Kafka. Understanding of telecom KPIs, customer journeys, and operational systems. Experience tuning and optimizing Spark workloads for enterprise-scale environments. Experience 8+ years of overall IT experience. 5+ years of hands-on experience in big data and ETL engineering.