Position: GCP Big Data Engineer Location: Philadelphia, PA(Onsite) Exp : 8+ Client: UMG Rate: $62 on W2 and $70 on C2C Net 60 days payment terms Job Description: We are seeking a highly skilled Senior GCP Big Data Engineer to join our team and work on cutting-edge data solutions for our client, UMG. The ideal candidate will have extensive experience in designing, building, and optimizing large-scale data pipelines on Google Cloud Platform (GCP) using PySpark, Apache Beam, Dataflow, and BigQuery. You will play a key role in processing and analyzing massive datasets to drive business insights. Key Responsibilities: • Design, develop, and optimize scalable Big Data pipelines using GCP services (Dataflow, BigQuery, Pub/Sub, Cloud Storage). • Implement real-time and batch data processing using Apache Beam, Spark, and PySpark. • Work with Kafka for event streaming and data integration. • Orchestrate workflows using Airflow for scheduling and monitoring data pipelines. • Write efficient Java/Python code for data processing and transformation. • Optimize BigQuery performance, including partitioning, clustering, and query tuning. • Collaborate with data scientists and analysts to enable advanced analytics and machine learning pipelines. • Ensure data reliability, quality, and governance across pipelines. • Leverage Google Analytics and GFO (Google for Organizations) where applicable. Required Skills & Experience: • 8+ years of hands-on experience in Big Data engineering. • Strong expertise in GCP (Google Cloud Platform) – Dataflow, BigQuery, Pub/Sub, Cloud Storage. • Proficiency in PySpark, Spark, and Java/Scala for Big Data processing. • Experience with Apache Beam for unified batch/streaming pipelines. • Solid understanding of Kafka for real-time data streaming. • Hands-on experience with Airflow for workflow orchestration. • Strong SQL skills and optimization techniques in BigQuery. • Experience with distributed computing and performance tuning. Good to Have: • Knowledge of GFO (Google for Organizations). • Familiarity with Google Analytics for data integration. • Experience with DataProc, Cloud Composer, or Dataprep. • Understanding of CI/CD pipelines for Big Data applications.