Data Engineering Manager - Build Scalable Pipelines & ML

twentysix; Jakarta Pusat; Hybrid; IDR 446,400,000 - 892,800,000; Full time

Job summary

Artefact is seeking a Data Engineer Manager in Jakarta to design and maintain robust data pipelines, utilizing Python and SQL for ETL across systems. You will manage databases, integrate cloud services (Azure, AWS, GCP), and collaborate with teams to embed ML models in data flows.

Responsibilities include building scalable data platforms, real‑time processing with Spark and Kafka, and mentoring engineers while engaging with business stakeholders in a dynamic startup-like environment.

Qualifications

• 8+ years of industry experience in data engineering.
• Proficiency in Python, SQL, and database management.
• Experience with ETL pipelines, Cloud Services (Azure, AWS, GCP), ML modeling, Spark & Kafka.
• Data modelling and modern data platform design concepts.
• Building and maintaining data platforms in Azure/AWS or GCP.
• Experience working with business stakeholders.
• Excellent communication and collaboration skills.
• Strong business acumen with startup mentality.

Responsibilities

• Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms.
• Database Management: Managing databases, ensuring integrity, and implementing data storage and retrieval solutions.
• Cloud Services Integration: Leveraging cloud services to architect and deploy scalable data solutions.
• Machine Learning Integration: Collaborating to integrate ML models into data pipelines.
• Utilising Spark & Kafka: Implementing real-time data processing and analytics.
• Mentor and guide engineers, fostering knowledge sharing and best practices.

Skills

Python

SQL

Data pipelines

Cloud services

ML modeling

Spark

Kafka

Communication

Education

Bachelor's degree in CS/EE/CE

Tools

Azure

AWS

GCP

Spark

Kafka

SQL Server

Job description

Artefact is seeking a Data Engineer Manager in Jakarta to design and maintain robust data pipelines, utilizing Python and SQL for ETL across systems. You will manage databases, integrate cloud services (Azure, AWS, GCP), and collaborate with teams to embed ML models in data flows.

Responsibilities include building scalable data platforms, real‑time processing with Spark and Kafka, and mentoring engineers while engaging with business stakeholders in a dynamic startup-like environment.