Principal Engineer Data Engineering

Verizon•Irvine, CA

2d•Remote

About The Position

When you join Verizon, you want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What you’ll be doing... As a Senior Data Leader, you will design, build, and optimize our enterprise data architecture to drive strategic insights and high-impact business decisions. You will lead the development of end-to-end data pipelines, manage cloud-based data warehouses, and integrate modern DevOps and automated workflows into our data ecosystem. Specifically, you will be responsible for: Designing and building scalable, high-performance ETL/ELT data pipelines from diverse source systems to cloud platforms. Architecting robust data models (conceptual, logical, physical) that support reporting, analytics, and advanced business applications. Managing and modernizing enterprise data storage , driving seamless performance across legacy data warehouses (such as Teradata) and modern cloud platforms. Implementing DevOps and CI/CD best practices for data pipelines to ensure continuous, automated, and reliable data delivery. Optimizing SQL queries, Python scripts, and orchestration workflows to improve system throughput and decrease processing latency. Evaluating and integrating innovative data technologies , including AI/ML automation and advanced orchestration tools, into our data infrastructure. Please note the location is flexible within the US

Requirements

Bachelor’s degree or four or more years of work experience.
Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
Five or more years of hands-on experience in ETL/ELT data pipeline development.
Demonstrated experience in Data Modeling, Data Warehousing, and System Architecture.
Expert-level proficiency in SQL and Python.
Hands-on expertise with cloud platforms (AWS and/or GCP).

Nice To Haves

A degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
Experience with workflow orchestration and integration tools such as Apache Airflow and Talend.
Strong familiarity with traditional data warehouse platforms like Teradata.
Proven background implementing DevOps practices for data (DataOps) using Git, Jenkins, and automated testing frameworks.
Experience leveraging AI/ML tools or generative AI techniques within data engineering workflows (e.g., automated data quality checks, smart ingestion, or AI-assisted code generation).
Cloud or Data Engineering certifications (e.g., AWS Certified Data Engineer, GCP Professional Data Engineer).

Responsibilities

Designing and building scalable, high-performance ETL/ELT data pipelines from diverse source systems to cloud platforms.
Architecting robust data models (conceptual, logical, physical) that support reporting, analytics, and advanced business applications.
Managing and modernizing enterprise data storage, driving seamless performance across legacy data warehouses (such as Teradata) and modern cloud platforms.
Implementing DevOps and CI/CD best practices for data pipelines to ensure continuous, automated, and reliable data delivery.
Optimizing SQL queries, Python scripts, and orchestration workflows to improve system throughput and decrease processing latency.
Evaluating and integrating innovative data technologies, including AI/ML automation and advanced orchestration tools, into our data infrastructure.