Job description for Data Engineer at KBB Automotive
Key Responsibilities
- Develop, maintain, and optimize data pipelines (ETL/ELT) to support production, quality control, supply chain, and other operational needs.
- Design data architecture to support real-time monitoring of production lines, machinery, and IoT devices using TimescaleDB or similar time-series databases.
- Manage and optimize relational databases such as PostgreSQL for analytics, reporting, and system integration.
- Implement and manage data workflow orchestration using Apache Airflow, ensuring automated and scheduled data processes run smoothly.
- Collaborate closely with production, maintenance, engineering, and quality teams to understand their data requirements.
- Ensure data integrity, quality, and security, and troubleshoot anomalies or pipeline failures.
- Create technical documentation for pipelines, data architecture, and system configurations.
- Support the implementation of IoT systems, MES, ERP, and other digital manufacturing platforms requiring data integration.
Qualifications
- Diploma or Bachelor's degree in Computer Science, Information Systems, Industrial Engineering, or related fields.
- Strong proficiency in SQL, including complex queries, optimization, and indexing.
- Experienced with PostgreSQL or other relational databases.
- Hands-on experience with TimescaleDB or other real-time / time-series databases (e.g., InfluxDB, Prometheus) is highly preferred.
- Familiar with Apache Airflow (DAG creation, scheduling, monitoring).
- Strong understanding of ETL/ELT concepts, data modeling, data warehousing, and modern data architecture.
- Experience with Python for data processing is a significant advantage.
- Experience working with production machine data, IoT sensors, or manufacturing environments is a plus.
- Strong problem-solving skills, detail-oriented, and comfortable working in a dynamic factory environment.
