Senior Data Engineer

Company 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.

Job Description

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 engineer in the Fulfillment Data Engineering team, you will work closely with product analytics, data scientist, software engineers and business stakeholders across the SEA in understanding the business and data requirements. You will be responsible for building and managing the data asset, including acquisition, storage, processing and consumption channels, and using some of the most scalable and resilient open source big data technologies like Flink, Airflow, Spark, Kafka and more on cloud infrastructure. You are encouraged to think out of the box and have fun exploring the latest patterns and designs.

The Day-to-Day Activities

• Design, develop, and maintain scalable real-time data processing pipelines using Apache Flink.
• Collaborate with cross-functional teams to understand data requirements and implement solutions.
• Optimize and monitor the performance of Flink jobs to ensure high availability and low latency.
• Build and manage ETL processes for data ingestion, transformation, and storage across distributed systems.
• Ensure data quality, consistency, and reliability by implementing validation and monitoring mechanisms.
• Troubleshoot and debug issues in data pipelines, ensuring seamless data flow across systems.
• Document technical solutions, processes, and workflows to ensure knowledge sharing within the team.

Qualifications

The Must-Haves

• 3+ years of hands-on experience in data engineering with a focus on Apache Flink.
• Proficiency in Java or Scala for Flink development.
• Strong understanding of real-time data processing concepts and event-driven architectures.
• Experience with message brokers like Apache Kafka and different databases – NoSQL, Columnar, Relational.
• Solid knowledge of distributed systems and big data technologies (e.g., Hadoop, Spark, etc.).
• Ability to debug and resolve complex issues in large-scale data systems.
• Strong verbal and written communication skills to collaborate with technical and non-technical teams.
• Bachelor's degree or higher in Computer Science, Engineering, or a related field.

The Nice-to-Haves

• Relevant certifications in Apache Flink or big data technologies.
• Contributions to open-source projects or active participation in the Apache Flink community.
• Basic understanding of ML pipelines and integrating data engineering workflows with ML models.
• A proactive mindset, adaptability to changing priorities, and eagerness to learn new technologies.

Additional Information

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.

Job Profile

Data Engineering 4