GRAB

Senior Data Engineer

Jakarta, Indonesia · On-site · Full-time

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About the role

Description from the employer’s posting. Check the employer’s page for the current version.

  • EmployerGRAB
  • LocationJakarta, Indonesia
  • Work styleOn-site
  • Employment typeFull-time
  • Employer posted

Get to Know the Role

As a Data Engineer in the Lending Data Engineering team, you will collaborate with a diverse group of stakeholders across Southeast Asia. This group includes data modelers, product analysts, product managers, software engineers, and business leaders. You will design and manage scalable, end-to-end data solutions across acquisition, storage, processing, and consumption. These solutions will utilize technologies like Flink, Airflow, Spark, Kafka, and Trino. You will report directly to the Data Engineering Manager, with a full-time onsite working arrangement in our Jakarta Office.

The Critical Tasks You Will Perform

  • Build and maintain scalable batch, real-time, and event-driven ETL pipelines using core AWS services (Glue, Redshift, Athena, Lambda, S3, EMR, Kinesis, MSK).
  • Design and deploy modern data lifecycle frameworks supporting streaming, API-based, serverless, and batch consumption directly on the data lake.
  • Establish robust data checks, automated cleansing routines, and governance best practices using tools like AWS Glue DataBrew to ensure high data reliability.
  • Monitor, maintain, and optimize data platform infrastructure to guarantee high availability, low latency, and accurate, timely delivery of key business metrics.
  • Master and leverage in-house data platform tools alongside native AWS technologies to streamline pipeline setup, execution, and real-time metric tracking.
  • Collaborate across engineering teams to translate real-time data availability into actionable business definitions, driving data-informed decision-making.
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What Essential Skills You Will Need

  • 6+ years building scalable, fault-tolerant, and mission-critical data pipelines.
  • Proficiency in Python, Scala, or Java; strong SQL, schema design, and data modeling skills.
  • Expertise in big data frameworks (Flink, Spark, Trino, Airflow, Kafka) across SQL, NoSQL, and Columnar databases.
  • Hands-on experience with AWS services (S3, EMR, Redshift, Athena, Glue, Kinesis) and event-driven architectures (SNS, SQS, Lambda).
  • Experience for analytical. Experience communicating updates and resolutions to customers and other partners with a drive to learn and innovate.
  • Degree in Computer Science, IT, Engineering, or a related technical field.
  • Solid grasp of Data Structures, Algorithms, or Machine Learning concepts.

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.
  • Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

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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At a glance

  • Work styleOn-site
  • Employment typeFull-time
  • SeniorityMid level
  • Employer posted
  • Added to ROLIVA
  • Last checked

Skills in this posting

Skills ROLIVA found in the employer’s own description above. A mention is not a requirement.

SQL Python AWS Java Scala Spark Airflow Kafka Machine learning

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