Job description for Data Engineer at Transnovasi Bangun Persada
Requirements
1. Minimum Bachelor's Degree (S1) in Information Technology, Information Systems, Computer Science, or a related field.
2. Minimum 4 years of experience as a Data Engineer.
3. Strong proficiency in Python and experience building ETL/ELT pipelines.
4. Strong knowledge of PostgreSQL, MongoDB, and TimescaleDB.
5. Good understanding of Data Warehouse, Data Cleansing, and Data Modeling.
6. Familiar with Docker, API Integration, and database query optimization.
7. Experience with AI, Qdrant, or LLM is an advantage.
8. Strong analytical, innovation, and accountability skills.
9. Strong communication, interpersonal, and problem-solving skills.
10. Have English language proficiency, with at least passive proficiency.
11. Placement: Head Office, East Jakarta.
Job Description
- Design, develop, and maintain ETL/ELT pipelines using Python to support data processing, transformation, and integration across multiple systems.
- Manage and optimize PostgreSQL, MongoDB, and TimescaleDB databases to ensure data availability, accuracy, and performance.
- Develop and maintain Data Warehouse architectures to support business intelligence, reporting, and data analytics requirements.
- Perform Data Cleansing, Data Transformation, and Data Modeling to ensure data quality, consistency, and reliability.
- Develop and maintain API integrations to enable seamless data exchange between internal and external systems.
- Perform database query optimization and performance tuning to improve data processing efficiency and system performance.
- Utilize Docker to support the deployment and management of data engineering applications and services.
- Support the integration and implementation of AI, Qdrant, or Large Language Model (LLM) technologies when required.
- Monitor, troubleshoot, and resolve data pipeline failures, database issues, and data inconsistencies to maintain reliable data operations.
- Collaborate with Software Developers, System Analysts, and other stakeholders to understand data requirements, deliver scalable data solutions, and support business objectives.
