Verizon Communications - Irving, TX
posted about 2 months ago
The Principal Data Engineer at Verizon is a pivotal role responsible for expanding and optimizing the company's data assets, data pipeline architecture, data flow, and data curation. This position plays a crucial part in enabling various network programs, including Network Performance Experience, Operational Excellence, and Workforce Optimization. The role combines IT expertise with architecture and design, requiring a comprehensive understanding of network service assurance and network operations data. This data will be utilized for Business Analytics, Operational Analytics, Text Analytics, Data Services, and the development of Big Data Solutions for different Verizon Business units. In this role, you will define and drive end-to-end data pipeline deployments, including creating a roadmap, designing the architecture, and ensuring execution excellence with metrics focused on business outcomes. You will also be responsible for driving data harmonization components that generate business value for network services and operations, enabling proactive actions in a timely manner. Additionally, you will support the building of prototypes and proof of concepts to validate integrated technologies and products, and then lead these POCs through to implementation. Oversight and collaboration on pipeline implementations will be essential to ensure governance, quality, and compliance. You will also lead junior team members, enhancing their technical and functional skills. Utilizing your in-depth understanding of data warehousing technologies, along with a broad knowledge of both on-premises and cloud deployments, you will help shape the future of the enterprise-wide network big data ecosystem. Meeting business objectives will involve delivering high-quality, on-time, and on-budget solutions by leveraging a global talent pool, including employees, T&Ms, and SOW labor. You will work closely with onshore teams to oversee the execution of tasks such as the development and population of data/ETL pipelines, testing results with end users, and providing operational support.