Distinguished Data Engineer

About the position

As a Distinguished Data Engineer at Verizon, you will manage data platforms and implement new technologies to enhance data science and analytics. Your role will involve driving the vision for data platform enrichment, providing technical leadership, designing complex data solutions, ensuring data quality, and collaborating with cross-functional teams to deliver impactful data-driven solutions.

Responsibilities

• Manage data platforms and implement new technologies to enhance data science and analytics.
• Drive vision for data platform enrichment covering Data Warehousing/Data Lake/BI across Verizon Business and Consumer Groups.
• Provide technical leadership and guidance, mentoring other engineers and influencing architectural decisions.
• Design and develop complex data solutions, including building and maintaining data pipelines, data warehouses, and data lakes.
• Leverage expertise in big data technologies and cloud platforms to deliver innovative AI & Data solutions.
• Implement robust data quality checks and validation processes to maintain data accuracy and reliability.
• Collaborate with data scientists, analysts, and business stakeholders to understand requirements and deliver solutions.
• Stay abreast of industry trends and explore emerging technologies in big data and cloud computing.

Requirements

• Bachelor's degree or four or more years of work experience.
• Six or more years of relevant work experience.
• Extensive experience in end-to-end delivery of Data Warehousing Solutions and large scale data transformation, preferably in telecom industry.
• Experience in building both batch & real-time data solutions using Google Cloud Platform/Big Query.

Nice-to-haves

• Six or more years of experience in leading teams and driving end-to-end deliverables.
• Two or more years of experience in contributing to the telecom/technology industry through white papers or articles.
• Experience in delivering Data Products at enterprise scale focused on B2B revenue generation and access cost models.
• Experience in building data services using conversational data and integrating with Generative AI services.
• Experience in building data products that enable predictive and prescriptive AI.
• Experience working with Graph DB or Vector DBs.
• Experience with DevOps and Data pipeline automation platforms.
• Knowledge of Spark, Hive, Scala, Pig, Kafka, Pulsar, Nifi, Python, Shell scripting.
• Knowledge of Data Governance and Data Quality.

Benefits

• Hybrid work environment with defined work location and work from home options.
• Minimum eight assigned office days per month.
• Diversity and inclusion initiatives.