About Grab and our workplace
Grab is Southeast Asia’s leading superapp. We are dedicated to improving the lives of millions of users across the region by providing them everyday services such as deliveries, mobility, financial services, enterprise services and others. More than that, we provide the opportunity for them to have a better life. And that aspiration starts inside Grab because we believe in a seamless blend of work and home life, making every aspect of life better for all.
Guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles—the 4Hs: Heart, Hunger, Honour and Humility—we work to create economic empowerment for the people of Southeast Asia. With our unwavering commitment to our values, we believe that we're more than a service provider; we're agents of positive change.
Get to know the Role:
As an engineer on the Customer Data Platform at Grab, you will be helping serve our mission to power personalization efforts by building a marketplace of customer attributes to enable audience creation and user grouping across all lines of business, whether in relation to passengers, driver partners, or merchants. Our customers span across teams and products, including marketing, ads, rewards, driver incentives, personalization, etc. You will work closely with a cross functional team of engineers on service and event driven architectures spanning real-time, batch, as well as offline workloads.
We are looking for a strong Full Stack Engineer who is proficient in both back end and front end development.
The day-to-day activities:
The must haves:
Tech Stack
The Customer Data Platform team uses Go for backend services, Kafka as an event log, Spark as a batch processing stack, ScyllaDB, DynamoDB, and RDS MySQL for data persistence, with a Redis for cache and Elasticsearch for full text search for segments. The frontend stack is built with Javascript using React. Our SDLC involves working with Terraform, GitLab, Jenkins, and a range of other internal tools, and operations involve working with AWS, Kibana, Datadog, and potentially Kubernetes.
This job is closed.