Service Development and Activation Engineer at Safaricom Kenya

JOB DESCRIPTION

• Reporting to the Manager - Service Activation, Enterprise Solutions Design & Implementation, the role of the Service Development and Activation Engineer is to design, test, and implement Internet of Things (IoT) services for Enterprise customers. Contribute in collaborative effort to develop, deliver and maintain technical aspects of IoT service for Enterprise customers.  This includes but not limited to SIM only connectivity activations, Networks, platforms, professional service, IoT device testing, Customer training, Process reviews, partner engagement and performance management.

RESPONSIBILITIES

• Lead and champion Enterprise IoT technology delivery for Enterprise customers.
• Lead and champion IoT capacity building effort to scale.
• Lead and motive for design of processes to design, deploy and operate IoT technologies for Enterprise customers.
• Define IoT Performance management metrics to measure success criteria and lead optimization efforts.
• Lead in identification, selection and management of IoT delivery and support partners for Enterprise customers.
• Lead collaborative effort with stakeholders to create IoT center of excellence, build competence for scale.
• Define, review and Optimize customer journey for Enterprise IoT services.
• Collaborate in the review and validation of IoT Architecture to ensure secure, reliable and resilient IoT service delivery for enterprise customers

QUALIFICATIONS

• Degree in BSc Computer Science, Telecoms, Electronic Engineering, Data Science or any other relevant qualification.
• Teamwork: Teamwork, Agile, Scrum, HW-SW codesign
• Business Intelligence: Streaming Analytics, Predictive Analytics, Hadoop, PowerBI, Tableau, Machine learning, Elastic Stack.
• UI/UX designer: Mobile UI, UX vs UI, Material design, Angular2, Front End, Javascript, CSS, Bootstrap, Basic colors.
• Mobile development: Android, IoS, Cordova, Meteor, BLE, Java.
• IP Networking: Routing, 
• Design for data: Big Data, MongoDB, Apache Cassandra, Spark, Elastic Stack
• ML/AI: Machine Learning, Deep Learning, AI, Neural Networks, TensorFlow