Senior Data Engineer: Build Scalable Data Pipelines

SmartRecruiters, Inc.; Petaling Jaya; On-site; MYR 180,000 - 240,000; Full time

Job summary

Grab's Data Engineering team builds the data backbone for a large-scale consumer platform. As a Senior Data Engineer, you'll design and scale data pipelines from source to decision, collaborating with product, business, and analytics teams to support reporting and data science use cases.

This onsite role involves ownership of production pipelines, ensuring data quality and SLA adherence while selecting technologies for dashboards and insights.

Qualifications

• 4+ years of experience in data engineering, building and operating production data pipelines at scale.
• Strong hands-on Python and SQL skills.
• Knowledge of PySpark, Presto, and Airflow.
• Solid understanding of ETL and layered data warehousing patterns.
• Fluency in written and spoken English.

Responsibilities

• You will leverage large volumes of data from internal sources across the business
• You will develop, maintain, and support production data pipelines (ETL, streaming, batch) using Python and SQL
• You will act as the engineering point of contact for business stakeholders, gathering and assessing their data needs
• You will ensure data architecture meets business and reporting requirements, including SLA commitments
• You will recommend ways to deliver quality data more efficiently and identify opportunities to add value
• You will run multiple concurrent pipeline projects and migrations from scoping through delivery
• You will work closely with backend engineers on source-system migrations — re-pointing and validating data pipelines during active platform cutovers — to ensure no data loss or SLA breach

Skills

Python

SQL

English

Big Data

ETL

Tools

PySpark

Presto

Airflow

Job description

Grab's Data Engineering team builds the data backbone for a large-scale consumer platform. As a Senior Data Engineer, you'll design and scale data pipelines from source to decision, collaborating with product, business, and analytics teams to support reporting and data science use cases.

This onsite role involves ownership of production pipelines, ensuring data quality and SLA adherence while selecting technologies for dashboards and insights.