We are seeking a skilled and motivated Data Engineer to design, build, and maintain robust and scalable data pipelines and infrastructure. As a key member of our data team, you will work closely with data scientists, analysts, and software engineers to ensure the reliable flow, storage, and accessibility of high-quality data across the organization.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines that integrate data from multiple sources.
• Build and manage data architecture using cloud-native tools on AWS to support analytics and machine learning workloads.
• Ensure data quality through validation, automated testing, and monitoring.
• Provide reliable, secure, and structured datasets for dashboards and reports using AWS QuickSight.
• Collaborate with data scientists to support machine learning model deployment and build robust data feeds for experimentation and production.
• Set up and maintain automated jobs using crontab or AWS scheduling tools like EventBridge or Step Functions.
• Monitor and troubleshoot pipeline failures; build alerting systems to ensure data pipeline health.
• Evaluate and recommend new technologies or tools to improve performance, scalability, and reliability of data systems.
• Document technical architecture, data lineage, and pipeline processes to promote transparency and maintainability.
• Work cross-functionally with analysts, developers, DevOps, and business stakeholders.

Requirements

• 2+ years of experience in Data Engineering, preferably in e-commerce, marketplaces, or high-scale environments.
• Bachelor’s degree in Computer Science, Information Technology, Mathematics, or a related technical field.
• Proficiency in Python and SQL for data transformation and automation tasks.
• Solid understanding of data modeling, data warehousing, and relational/dimensional data design.
• Experience with ETL/ELT pipelines, debugging data issues, and handling structured/unstructured data.
• Experience in web scraping and integrating scraped data into data pipelines.
• Strong working knowledge of AWS Data Services, including: S3, Glue, Athena, DMS, RDS, Sagemaker, Lambda, and Quicksight
• Familiarity with job scheduling tools, including crontab or AWS-native alternatives like EventBridge.
• Experience using version control systems, especially Git (GitLab, GitHub).
• Proven ability to collaborate with data scientists to support machine learning lifecycle and data preparation.
• Interest in exploring new tools and helping improve our data architecture.

Placement : Head Office Kawan Lama, West Jakarta

About Kawan Lama Group

Established in 1955, Kawan Lama Group is a multi-sector group of companies who are constantly innovating for improving the quality of lives. Manages 28 brand portfolios operating in six different sectors: Commercial & Industrial, Consumer Retail, Food & Beverages, Property & Hospitality, Manufacturing & Engineering, and Commercial Technology. Aiming to be more than family business - but beyond that, we are business for families, we carry the mission to bring values for betterment of lives through business development and continuous growth.