Senior Engineer (Data)

Pertama Partners; Kuala Lumpur; On-site; MYR 100,000 - 150,000; Full time

Job summary

Pertama Partners in Kuala Lumpur is seeking a Data Engineer to build and optimize data infrastructure for AI applications. You will design and implement data pipelines, build APIs, and monitor system performance. Ideal candidates should have over 5 years of experience in production data systems and strong skills in Python and SQL. This role offers the opportunity to work on impactful projects for Fortune 500 companies with a fast-paced, innovative culture.

Qualifications

• Minimum of 5 years experience in building production data systems including pipelines, warehouses, and APIs.
• Strong proficiency in programming languages such as Python and SQL.
• Experience with distributed systems and effective data modeling.

Responsibilities

• Design and implement data pipelines for AI applications.
• Build and serve APIs for ML models and analytics.
• Optimize database queries and improve schema for scalability.

Skills

Python

SQL

Data modeling

Debugging

Tools

Docker

AWS

dbt

Airflow

Spark

Job description

Build data infrastructure for AI products at enterprise scale

full-time

Highly competitive

Overview

Build the data backbone for AI applications used by millions. You'll design pipelines that ingest messy enterprise data, transform it into clean datasets, and serve it through performant APIs. Work spans the full stack: database schema design, ETL pipelines, API development, query optimization. You'll make architectural decisions that directly impact product performance and reliability.

Responsibilities

• Design and implement data pipelines for client AI applications
• Build APIs that serve ML models and analytics dashboards
• Optimize database queries and schema for scale
• Debug data quality issues and implement validation logic
• Monitor system performance and respond to incidents
• Code review and mentor junior engineers

Requirements

• 5+ years building production data systems (pipelines, warehouses, APIs)
• Strong proficiency in Python and SQL
• Experience with distributed systems and data modeling
• Track record shipping features to production used by real users

Preferred Qualifications

• Built systems processing millions of events per day
• Experience with modern data stack (dbt, Airflow, Spark)
• Worked in fast-growing startups or high-performance teams
• Contributions to open-source data projects

Nice to Have

• Docker
• AWS

A Day in the Life

Morning: Debug slow query in client dashboard. Mid-morning: Design review for new pipeline architecture. Afternoon: Implement incremental ETL for real-time feature. Late afternoon: Code review and pair programming session.

Why This Role

Work on systems that matter. See your code run in production at Fortune 500 companies. Learn from senior engineers who've built infrastructure at scale. Ship fast without bureaucracy.