Analytics & AI Engineer - Data Platform & ML Ops

Wego.com; Daerah Khusus Ibukota Jakarta; On-site; IDR 300,000,000 - 600,000,000; Full time

Job summary

Wego.com is seeking an Analytics + AI Engineer to join our Data Analytics & Data Science team in Jakarta. You will architect data infrastructure, build AI-enabled systems, and collaborate with data scientists to translate needs into scalable pipelines and production services.

You will work on ensuring data quality, reliability, and smooth productionization of models, while advancing cross-team collaboration and the overall analytics platform.

Qualifications

• 3–8 years of experience in data engineering, platform engineering, or ML infrastructure.
• Strong understanding of data warehouse architecture, pipeline orchestration, and ML Ops.
• Experience building analytics or data platforms that support both human users and automated systems.

Responsibilities

• Data Warehouse & Orchestration — Design and build a modern, well-orchestrated data warehouse and pipeline architecture.
• Reliability & Data Quality — Build alerting, monitoring, and data-quality checks so the data platform can be trusted across the business.
• Model Productionization — Turn statistical and machine learning models into reliable, scalable production services.
• AI / Agent Enablement — Build the ML Ops stack and tooling and context layers that let AI agents operate on our data reliably.
• Cross-Team Partnership — Work closely with data scientists and analysts to translate their needs into architecture and tooling decisions.

Skills

SQL

Python

AI/Agent engineering

Data warehousing

ML Ops

Data pipelines

Tools

Google Cloud Platform

AWS

Azure

BigQuery

Job description

Wego.com is seeking an Analytics + AI Engineer to join our Data Analytics & Data Science team in Jakarta. You will architect data infrastructure, build AI-enabled systems, and collaborate with data scientists to translate needs into scalable pipelines and production services.

You will work on ensuring data quality, reliability, and smooth productionization of models, while advancing cross-team collaboration and the overall analytics platform.