Design, develop and maintain backend infrastructure, workflows, and services for enabling easy to use solutions for Customer Support organizations within service providers.
Develop solutions to support onboarding, partner integrations, managing, collecting, and analyzing data from large scale deployment of home networks and make them available as actionable insights to CSRs.
Work closely with Cloud product owners to understand, analyze product requirements, provide feedback, and deliver a complete solution.
Technical leadership of software design in meeting requirements of service stability, reliability, scalability, and security
Participate and drive technical discussions within engineering group in all phases of the SDLC: review requirements, produce design documents, participate in peer reviews, produce test plans, support QA team, provide internal training and support TAC team.
Support test strategy and automation in both end-to-end solution and functional testing.
Customer facing engineering role in debugging and resolving field issues.
Qualifications:
10+ years of highly technical, hands-on software engineering experience
Independent and Self driven and works in a Team.
Strong, creative problem-solving skills and ability to abstract and share details to create meaningful articulation.
Ability to drive technical discussions across x-functional teams.
Proficient in design and implementation of microservices-based, API/Endpoint architectures
Strong background in designing and developing event-based / pub-sub workflows data ingestion solutions. Proficiency and hands on experience with Kafka at scale (or similar) desired.
Experience in/Knowledge of protocols technologies for managing home gateways (TR-069/TR-369, TR-98/TR-181), in-home services, monitoring and efficiently curating data from millions of IoT/Wi-Fi devices a plus.
Good understanding of implementation and deployment of Cloud based solutions (preferably AWS)
Strong background in transactional databases and good understanding and experience with no-SQL datastores.
Expert in Java. Proficiency in other languages like Go, Python, NodeJS/JavaScript a plus.
Organized and goal-focused, ability to deliver in a fast-paced environment.
Experience in designing batch-based, low latency real-time streaming and event-based data solutions (Kafka, Storm, Spark, Flink, Kinesis or like technologies).
Organized and goal-focused, ability to deliver in a fast-paced environment.
Experience building scalable solutions and in choosing the right data store technologies for data analytics (Cassandra, Elastic, Greenplum, Redshift).
Practical understanding and usage of AWS (or Azure) Cloud platform and services.
