[959] Back End Developer

Job Details

• Self-managing and contributing to the product development activities including both internal projects and joint development projects;
• Conducting end-to-end analysis that includes data gathering and requirements specification, analysis, and ongoing deliverables;
• Writing back-end APIs in Go to manage automated data analytics and machine learning pipelines and training systems, and serve machine learning models on top of Kubernetes;
• Developing and optimising data analysis and transformation Spark applications in Scala/Python;
• Working with the Product and Data Science teams to brainstorm, design the architecture, evaluate technologies, implement POCs, benchmark and productionise the ideas;
• Designing and developing high-level SDKs, sample codes in Python/Java on top of auto-generated gRPC APIs of the platform;
• Building and testing in local/development environment, containerising and deploying applications or services to Kubernetes using Helm charts and GitOps tools;
• Working with the Sales and Marketing team to understand the requirements and support our clients;
• Mentoring and providing training to associate/junior software engineers and interns, motivating them to reach the next level;
• Participating in technical content writing. This may be in the form of product documentation, blog articles highlighting new features and use cases, as and when the need arises;
• Understanding and advocating our long-term vision while working with the management and product teams to define and adapt the same; and
• Contributing to the evangelisation of our product and our culture internally and externally

Job Requirements

• Be able to write well-designed, testable, and efficient code, and have extensive experience in writing unit tests and acceptance tests;
• In-depth knowledge of at least one of the following programming languages: Java, Go, Scala, and Python. The experience of using front-end frameworks such as Angular is very useful;
• Have a solid knowledge of at least one NoSQL database (such as Mongo) and containerization and orchestration tools (such as Docker and Kubernetes);

• Have a good understanding of functional and reactive programming paradigms, distributed and parallel processing, microservice architecture and event-driven architecture;
• Skills in at least one public cloud provider (such as GCP, AWS or Azure);
• Highly appreciate the basic knowledge of data engineering and machine learning systems;

• Proven ability to analyze, troubleshoot, and accelerate software implementation;
• Track record with practical experience in modern software engineering methods (preferably more than 4 years).