Data Engineer

Data Engineer Location: Irving, TX | Alpharetta, GA | Basking Ridge, NJ 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.