Principal Member Tech Staff

Job Description:

POSITION:                 Principal Member Tech Staff

JOB LOCATION:       208 S Akard Street Dallas, TX 75202 [and various unanticipated locations throughout the U.S.; may work from home]

Principal Member Tech Staff needed by AT&T Services, Inc. in Dallas, TX [and various unanticipated locations throughout the U.S.; may work from home] to develop solutions to complex business and technical problems and issues of complex scope with advanced engineering and scientific principles. Apply engineering principles and practice in broad areas of complex technical project work that requires in-depth analysis with advanced techniques, knowledge, and expertise. Drive projects end to end with hands-on technical experience and in-depth knowledge across multiple enterprise service assurance systems and platforms. Support network change management and planned network maintenance, including customer notifications integrated with fault management and performance management systems using service oriented architecture. Work with business partners to provide technical solutions. Advise on company technologies, systems, and procedures. Provide subject matter expert in change management and service assurance. Develop, enhance, and maintain large scale applications such as the company’s virtual trouble management with complex interfaces, and large volume of data, transactions, and maintenance lifecycle. Implement automation with workflow engines and APIs to increase operations efficiency, revenue generation, and improve client experience and satisfaction. Define optimal design patterns and solutions for high availability and disaster recovery for applications. Provide architectural leadership related to domain driven design and event streaming microservices. Provide technical expertise on internet security threats and mitigation techniques within project teams, and lead projects of small to medium size and technical breadth. Perform in-depth technical analysis. Provide database and data analytics modeling with expert knowledge in database technologies MongoDB, MariaDB, and Cassandra. Analyze large volume ticket data to categorize root cause issues and identify automation opportunities for various service assurance ticketing and customer facing initiatives. Provide statistical analysis, predictive modeling, anomaly detection, and trending analysis. Examine large volume of ticket data points, impacted customers, and identify multiple process improvements, and automation. Improve impacted customer data management across multiple systems and speed-up customer notification process. Conduct performance and security testing. Contribute to the development of advanced technologies and concepts with global reach and industry application. Using machine learning techniques, data structures, algorithms, and statistics. Develop frameworks for machine learning models integration with application and CI/CD pipelines. Integrate expert knowledge of technical principles and methods of multiple disciplines with knowledge of products, services, and internal operations. Work with Java/J2ee, Python, Spring boot, Apache Spark, Kafka, Redis, Redis Streams, Mongo, Apache Flink, Azure Kubernetes Service, Azure devops, Azure App gateway, and Azure IaaS/PaaS. Utilize AWS IaaS/PaaS, Elastic Kubernetes service, Docker, Elasticsearch, Apache Solr, Neo4j, Cassandra, Drools, Oracle, PL/SQL MySQL, Prometheus, Grafana, Anaconda Python, JavaScript, Jira, UML, JiraAlign, Unix, Linux, Windows, SonarCube, and Postman.

MINIMUM REQUIREMENTS: Requires a Bachelor’s degree, or foreign equivalent degree, in Computer Engineering or Information Technology and five (5) years of progressive, post-baccalaureate experience in the job offered or five (5) years of progressive, post-baccalaureate experience in a related occupation applying engineering principles and practicing in broad areas of complex technical project work that requires in-depth analysis with advanced techniques, knowledge, and expertise; contributing to the development of advanced technologies and concepts with global reach and industry application; using machine learning techniques, data structures, algorithms, and statistics; developing frameworks for machine learning models integration with application and CI/CD pipelines; integrating expert knowledge of technical principles and methods of multiple disciplines with knowledge of products, services, and internal operations; working with Java/J2ee, Python , Spring boot, Apache Spark, Kafka, Redis, Redis Streams, Mongo, Apache Flink, Azure Kubernetes Service, Azure devops, Azure App gateway, and Azure IaaS/PaaS; and utilized AWS IaaS/PaaS, Elastic Kubernetes service, Docker, Elasticsearch, Apache Solr, Neo4j, Cassandra, Drools, Oracle, PL/SQL MySQL, Prometheus, Grafana, Anaconda Python, JavaScript, Jira, UML, JiraAlign, Unix, Linux, Windows, SonarCube,