Big Data Architect - Google Cloud at Verizon Communications in Piscataway, NJ
When you join Verizon Verizon is one of the world's leading providers of technology and communications services, transforming the way we connect across the globe. We're a diverse network of people driven by our shared ambition to shape a better future. Here, we have the ability to learn and grow at the speed of technology, and the space to create within every role. Together, we are moving the world forward - and you can too. Dream it. Build it. Do it here. What you'll be doing At Verizon, we are on a multi-year journey to industrialize our data practices and AI capabilities. Very simply, this means that AI and data will fuel all decisions and business processes across the company. At $130B
in annual revenue, this is a pioneering opportunity to build the data products and talent at a top global telco organization. With our leadership in bringing 5G networks nationwide, the opportunity for AI and Data will only grow exponentially in going from enabling new revenue opportunities and exquisite customer experience through real-time data insights. The Senior Level Big Data Architect - Google Cloud role is a blend of advanced analytics, strategy and leadership within Artificial Intelligence and Data (AI&D) organization responsible for developing and driving the execution of strategies to streamline the data acquisition i.e. collecting the data from transaction systems (Global Technology Solutions, Global Network and Technology and 3rd party vendors) and storing the data into data warehouses, data lakes and public/private cloud platforms.
Responsibilities:
Design and develop platform standards, common reference architecture and data governance policies, perform vendor/tool comparisons and present recommendations. Responsible for leading network data engineering from data sourcing, ingestion, and exposing the data for AI/ML model development, curation and data production. Partner with internal business partners in gathering business requirements and developing data engineering pipelines. Strategic thinker with ability to apply business mindset to data issues and initiatives, craft cross-business strategies and plans for multiple stakeholders. Participation in technology and industry forums on evolving data engineering, Data Science/ ML engineering/Ops practices to deploy new ML solutions. Active engagement with AI&D data engineering teams to bring synergies, align strategy and best practices and contribute to the capability roadmaps for data platforms. Prepare presentation materials and formal documents for use with senior management to promote findings and drive discussions. Responsible for monitoring the code and overall application to ensure seamless performance. Strong leadership, communication, persuasion and teamwork skills. In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. What we're looking for You'll need to have:
Bachelor's degree or four or more years of work experience. Six or more years of relevant work experience. Even better if you have:
Bachelor's or Master's degree in quantitative and/or technology disciplines such as Mathematics, Statistics, Data Analytics, Computer Science or Engineering. Programming experience in GCP Dataproc, GCS, Cloud functions and BigQuery for ETL related jobs. Experience in designing and deployment of Hadoop cluster and different big data analytical tools including HDFS, PIG, Hive, Sqoop, Spark, Oozie. GCP Data certification. Experience in collaborating with data engineers, architects, data scientists and enterprise platform team in designing and deploying data products and ML models in production Experience in developing, managing cloud implementations, upgrades, migrations (on-prem to cloud) and change requests on client cloud environments. Understanding of best practices for building Data Lake and analytical architectures on Hadoop, Teradata and public cloud infrastructure. Experience in enabling AI/ML model development, data curation and developing data products. Experience with Model Lifecycle management and governance experience to drive best-in-class data driven decisions. Ability to apply business mindset to data issues and initiatives. Experience in Google Data catalog and other google cloud APIs for monitoring, querying and billing related analysis for Big Query usage. Good communication, executive presentation and influencing skills.
Salary Range:
$100K -- $150K
Minimum Qualification
Data Science & Machine Learning, Business Intelligence & AnalyticsEstimated Salary: $20 to $28 per hour based on qualifications.
in annual revenue, this is a pioneering opportunity to build the data products and talent at a top global telco organization. With our leadership in bringing 5G networks nationwide, the opportunity for AI and Data will only grow exponentially in going from enabling new revenue opportunities and exquisite customer experience through real-time data insights. The Senior Level Big Data Architect - Google Cloud role is a blend of advanced analytics, strategy and leadership within Artificial Intelligence and Data (AI&D) organization responsible for developing and driving the execution of strategies to streamline the data acquisition i.e. collecting the data from transaction systems (Global Technology Solutions, Global Network and Technology and 3rd party vendors) and storing the data into data warehouses, data lakes and public/private cloud platforms.
Responsibilities:
Design and develop platform standards, common reference architecture and data governance policies, perform vendor/tool comparisons and present recommendations. Responsible for leading network data engineering from data sourcing, ingestion, and exposing the data for AI/ML model development, curation and data production. Partner with internal business partners in gathering business requirements and developing data engineering pipelines. Strategic thinker with ability to apply business mindset to data issues and initiatives, craft cross-business strategies and plans for multiple stakeholders. Participation in technology and industry forums on evolving data engineering, Data Science/ ML engineering/Ops practices to deploy new ML solutions. Active engagement with AI&D data engineering teams to bring synergies, align strategy and best practices and contribute to the capability roadmaps for data platforms. Prepare presentation materials and formal documents for use with senior management to promote findings and drive discussions. Responsible for monitoring the code and overall application to ensure seamless performance. Strong leadership, communication, persuasion and teamwork skills. In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. What we're looking for You'll need to have:
Bachelor's degree or four or more years of work experience. Six or more years of relevant work experience. Even better if you have:
Bachelor's or Master's degree in quantitative and/or technology disciplines such as Mathematics, Statistics, Data Analytics, Computer Science or Engineering. Programming experience in GCP Dataproc, GCS, Cloud functions and BigQuery for ETL related jobs. Experience in designing and deployment of Hadoop cluster and different big data analytical tools including HDFS, PIG, Hive, Sqoop, Spark, Oozie. GCP Data certification. Experience in collaborating with data engineers, architects, data scientists and enterprise platform team in designing and deploying data products and ML models in production Experience in developing, managing cloud implementations, upgrades, migrations (on-prem to cloud) and change requests on client cloud environments. Understanding of best practices for building Data Lake and analytical architectures on Hadoop, Teradata and public cloud infrastructure. Experience in enabling AI/ML model development, data curation and developing data products. Experience with Model Lifecycle management and governance experience to drive best-in-class data driven decisions. Ability to apply business mindset to data issues and initiatives. Experience in Google Data catalog and other google cloud APIs for monitoring, querying and billing related analysis for Big Query usage. Good communication, executive presentation and influencing skills.
Salary Range:
$100K -- $150K
Minimum Qualification
Data Science & Machine Learning, Business Intelligence & AnalyticsEstimated Salary: $20 to $28 per hour based on qualifications.
|
|
 | |
