Data Engineer

Requirements

• Minimum Bachelor’s Degree (S1) in Information Technology, Information Systems, Computer Science, or a related field.
• Minimum 4 years of professional experience as a Data Engineer or in a closely related role.
• Strong proficiency in Python, particularly for data processing, automation, and pipeline development.
• Proven experience in designing and building ETL/ELT pipelines.
• Strong knowledge and hands-on experience with PostgreSQL, MongoDB, and TimescaleDB.
• Good understanding of Data Warehouse, Data Cleansing, and Data Modeling concepts.
• Familiar with Docker, API Integration, and database query optimization.
• Experience with AI, Qdrant, and/or Large Language Models (LLM) will be an advantage.
• Able to work with large and complex datasets with strong attention to data quality and accuracy.
• Strong analytical thinking, innovation, accountability, and problem-solving skills.
• Strong communication and interpersonal skills, with the ability to collaborate effectively across teams.
• Have English language proficiency, with at least passive proficiency.
• Willing to work full WFO at Head Office, East Jakarta.

Job Description

• Design, develop, and maintain reliable and scalable ETL/ELT data pipelines to support business and system requirements.
• Collect, process, transform, and integrate data from various sources into databases and/or Data Warehouse.
• Perform data cleansing, validation, and transformation to ensure data accuracy, consistency, and quality.
• Design and maintain efficient data models and database structures for large-scale datasets.
• Develop and maintain solutions using Python for data processing and automation.
• Manage and optimize databases, including PostgreSQL, MongoDB, and TimescaleDB.
• Perform database query optimization and troubleshoot data processing or database performance issues.
• Develop and maintain API integrations to support data exchange between systems and applications.
• Utilize Docker to support application and data pipeline deployment environments.
• Collaborate with Developers, System Analysts, and other relevant teams to identify data requirements and deliver effective data solutions.
• Monitor data pipelines and resolve issues to ensure reliable and continuous data processing.
• Explore and support the implementation of AI, Qdrant, LLM, or other emerging data technologies when required.
• Maintain technical documentation related to data pipelines, database structures, integrations, and data processes.