Good Programming skills with any of Python, Golang, Scala, Java language. Hands on Experience in shipping the application to production (e.g. db, REST API's) Familiarity with the whole web stack, web protocols, and web performance optimisation techniques Detailed knowledge of minimum one modern JavaScript framework: React, Ember, Angular, etc Proficient understanding of the HTTP protocol Knowledge of relational databases and SQL; Experience in working on Big Data technologies like Hadoop, Spark is a plus. Quick learner and good team member with a positive attitude. Good verbal and written communication skills. Duties and Responsibilities: Design and implement RESTful APIs. Build and deploy performant modern web applications in React, NodeJS and TypeScript. Architect efficient backend systems for the data platform. Developing automation framework using programming languages such as python and automate the big data workflows such as ingestion, aggregation, ETL processing etc Debugging and troubleshooting issues within the big data platform. Define the operating procedures, service monitors and alerts and work with the infra team to get them implemented. Solve problems and establish plans and provide technical consultation in the design, development and test effort of complex engineering projects. Write unit, functional and end-to-end tests. Recreate complex customer and production reported issues to determine root cause and verify the fix. Identifies issues and technical interdependencies and suggests possible solutions. Qualifications: A degree or higher in Computer Science, Electronics or Electrical Engineering, Software Engineering, Information Technology or other related technical disciplines Well versed in setting up continuous integration and production development Experience in container management and orchestration tools like ECS, Kubernetes, and Mesos is a strong plus Experience in Big Data Technology such as Hadoop, Kafka and Spark is a plus Real passion for data, new data technologies, and discovering new and interesting solutions to the company's data needs Deep understanding on databases and best engineering practices - include handling and logging errors, monitoring the system, building human-fault-tolerant pipelines, understanding how to scale up, addressing continuous integration, knowledge of database administration, maintaining data cleaning and ensuring a deterministic pipelin
