Senior Data Engineer, Integrity Data Platform

  • Full-time

Company Description

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and Al to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

Job Description

Get to know our Team:

The Trust team is the custodian of integrity at Grab. We build modern solutions designed to provide fraud detection service with petabyte-scale datasets. Our platform uses the latest advancements in machine learning and artificial intelligence to help businesses minimize the risk of fraud and maintain a secure environment. We're committed to building a diverse team of passionate professionals who are dedicated to shaping the future of fraud detection technology, and prevent risks like Account Takeover, Chargeback, Fake Orders with automated solutions.

Get to know the Role:

You will report into the Senior Engineering Manager and be based onsite in Malaysia. Data Engineers in Grab get to work on one of the largest and fastest growing datasets of any company in South East Asia. We operate in a to push you to grow.

As a Senior Data Engineer for the Integrity Data Platform, you'll be at the forefront of our daily protection systems, finding ways to find useful signals from the petabytes of raw data in both offline batch and online streaming systems. This is an opportunity to explore one of the richest datasets in SouthEast Asia, and find signals that can create measurable impact. You will report directly to the Senior Engineering Manager, Integrity Data Platform.

The Critical Tasks You will Perform

  • Develop comprehensive data pipelines for real-time ML models and rules.
  • Enhance platform security using large-scale big data systems and data processing frameworks like Spark and Flink.
  • Manage data ingestion from streaming and batch systems, and build ETL jobs.
  • Implement scripts, ETL jobs, and data models in collaboration with data scientists, analysts, and machine learning engineers.
  • Participate in technical and product discussions and code reviews, providing on-call support.

Qualifications

What Skills You will Need

  • Educational Background: Hold a Bachelor's degree in a related technical field.
  • Experience: At least 4 years of experience in Big Data applications.
  • Big Data Frameworks: Proficient in frameworks like Hadoop, Spark, and Flink. You will leverage these technologies for data processing.
  • Programming Skills: knowledge of SQL in a MPP OLAP database, and experience with static programming languages like Java, Scala, Golang, or Rust. These skills are important for developing efficient data pipelines.
  • Collaboration and Independence:, demonstrating both independent initiative and teamwork.

Additional Information

Life at Grab

  • We care about your well-being at Grab, here are some of the global benefits we offer:
  • We have your back with Term Life Insurance and comprehensive Medical Insurance.
  • With GrabFlex, create a benefits package that suits your needs and aspirations.
  • Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
  • We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.

 

What We Stand For at Grab

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

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