Job Description

Responsibilities:
Lead the R&D team for new platform development.
Work closely with Senior Devs Manager and stakeholders to design the technical architecture to meet the requirements of the proposed solution which translate business requirements into specifications and detailed designs.
Collaborate with the team to produce high-quality code that allow us to put solutions into production, confidently ship large features and improvements.
Provide leadership in software engineering best practices to help team grow in their technical responsibilities. This include agile development methodologies, service architectures and design patterns and all phrases of software development lifecycle.
Enable team to incrementally deliver production results on a daily basis, highlight process bottlenecks and automation potential to optimize the teams' productivity.
Ensure Data completeness, consistency, accuracy, validity and timeliness.

Requirements:
Bachelor's Degree/Diploma in Computer Science, Information Technology or a related subject.
3 ~ 5 years of industry experience in related field leading development teams.
Fluent in fundamental Computer Science concepts, from algorithms and design patterns, over database paradigms and frontend technologies to scalable systems.
Know when to apply the latest developments in architectural patterns and technologies, specifically in open-source and across frontend and backend.
Expert in engineering lifecycles and related practices including continuous integration and continuous Deployment.
Still hand-on with team in technical discussions and code reviews but also by developing and deploying own code on a daily basis.
Proven track record in leading teams and building large-scale date pipeline.
Ability to perform data analysis and explain complex technical data concepts in context of solving business problem.
Strong Experience with .Net Core, C#, NodeJS, AngularJS, Microsoft SQL server, MySQL, APIs, Rabbit MQ
Experience in cloud-native microservices software design and development.
Have exposure in Docker containers, Kubernetes.
Experience in Real-time stream processing engine like Confluent Kafka, AWS Kinesis.