Data Engineer

Start Date: ASAP Interview Process: Three rounds, including one onsite/final face-to-face interview. Role Overview We are seeking an experienced Data Engineer to join Verizon's Data Engineering team supporting chatbot and IVR analytics initiatives. The ideal candidate will have a strong background in designing and building scalable data engineering solutions, developing robust data pipelines, and enabling analytics through modern cloud-based data platforms. This team is also building a next-generation Semantic Layer to improve data accessibility and business insights. Key Responsibilities Design, develop, and maintain scalable data pipelines for enterprise data processing. Build and optimize dashboards, reporting solutions, and analytical datasets. Develop and enhance data models that power the organization's Semantic Layer. Support data architecture, data integration, and engineering initiatives for chatbot and IVR analytics. Optimize data workflows to ensure performance, scalability, and data quality. Collaborate with cross-functional teams to understand business requirements and deliver reliable data solutions. Required Skills Strong hands-on experience with Python , including Apache Airflow for workflow orchestration. Advanced SQL skills with expertise in writing and optimizing complex queries. Experience working with Google BigQuery . Solid background in Data Engineering , including ETL/ELT development and large-scale data pipeline design. Experience building scalable cloud-based data solutions and supporting analytics platforms. Preferred Qualifications Experience working in the telecommunications or subscription-based industry . Familiarity with customer analytics, chatbot, IVR, or customer experience data platforms is a plus. Ideal Candidate The ideal candidate is a hands-on Data Engineer with strong expertise in Python, Airflow, SQL, and Google BigQuery , capable of building high-performance data pipelines and supporting enterprise analytics initiatives. Experience with semantic data modeling, customer analytics, or telecommunications environments will be highly valued. #J-18808-Ljbffr