Job Description

Life at Grab At Grab, every Grabber is 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. These principles guide and help us make decisions as we work to create economic empowerment for the people of Southeast Asia. Get to Know the Team The Fulfillment tech family is one of the pillars enabling Grab to out-serve our customers and partners in different businesses and marketplaces across Southeast Asia. We are working on high throughput, real-time distributed systems that use advanced software engineering techniques to solve hundreds of millions of requests per day. We are a distributed team in 4 different locations: Singapore, Beijing, Indonesia, and Malaysia. Our communication is in English, both in spoken and written form. Our mission is to offer the best-in-class products and experiences to our driver partners as to increase adoption and engagement of our services. Improve driver partner opportunities and efficiency in order to fulfill customer orders without fail, rain or shine. And to create efficient marketplaces by determining an optimal price that is both sustainable and loved by our partners and customers Get to Know the Role As the Data Modeler in the Fulfillment Data Engineering team, you will work closely with product analytics, product managers, data/software engineers, and business stakeholders across the SEA in understanding the business and data requirements. You will be responsible for designing and creating data models to support both real-time and offline metrics to measure the marketplace and ensure data integrity, consistency, and compliance with industry standards and best practices. You are encouraged to think out of the box and have fun exploring the latest patterns and designs. The Day-to-Day Activities: Formulating the conceptual and logical data models that define how data is organized, stored, and related. Developing a deep understanding of real-time data production availability to inform on the real-time metric definitions. Regularly updating and refining data models to accommodate changing business needs and new technology trends. Design and deliver the next-gen data lifecycle management suite of tools/frameworks, including ingestion and consumption on the top of the data lake to support real-time, API-based, and serverless use cases, along with batch as relevant. Apply core software engineering and design concepts in creating operational as well as strategic technical roadmaps for business problems that are vague/not fully understood. Obsess security by ensuring all the components, from a platform, and frameworks to the applications are fully secure and are compliant with the group\'s infosec policies. The Must-Haves: At least 8+ years of relevant experience in designing, creating, and maintaining the structure of a data management system. You have a degree or higher in Computer Science, Electronics or Electrical Engineering, Software Engineering, Information Technology, or other related technical disciplines Experience working on data architecture design for a project that was successfully delivered. Strong ability on communication skills especially cross-cultural, project management, and cross-team cooperation. Proficiency in data modeling tools to design and maintain data models. Familiarity with the business domain and processes helps in creating accurate and relevant data models. Proficiency in at least one of the programming languages Python, Scala, or Java. Strong understanding of big data and related technologies like Flink, Spark, Airflow, Kafka, etc. Experience with different databases - NoSQL, Columnar, Relational. You have a hunger for consuming data, new data technologies, and discovering new and innovative solutions to the company\'s data needs. . You are organized and insightful and can communicate your observations well, both written and verbally, to your stakeholders to share updates and coordinate the development of data pipelines. The Nice-to-Haves: You understand Data Structure, Algorithms, or Machine Learning models well. Our Commitment We recognize that with these individual attributes come different workplace challenges, and we will work with Grabbers to address them in our journey towards creating inclusion at Grab for all Grabbers.

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