- Design, build, and maintain scalable data infrastructure and ELT pipelines to deliver secure, real-time operational and supply chain data.
- Ensure high data quality, performance, and system availability while integrating multiple platforms (WMS, TMS, ERP, IoT).
- Monitor latency, query performance, and issue resolution, and drive automation to reduce manual effort.
- Maintain governance through access controls, audit readiness, and version-controlled SQL processes, enabling accurate reporting, advanced analytics, and efficient decision-making.
Minimum Requirements:
Minimum Requirements (Experience & Qualifications)
- Diploma / Degree in Computer Science or related field
- Microsoft Certified: Azure Data Engineer Associate
- Google Professional Data Engineer
- AWS Certified Data Analytics
- Certifications in BI or analytics tools (e.g. Power BI, Tableau, SQL)
- 3–5 years’ experience in data engineering, preferably in logistics and supply chain sectors
Required Knowledge:
- Design and develop scalable ELT/ETL pipelines using tools like Apache Airflow, SSIS, or Azure Data Factory.
- Integrate and model data across logistics systems (ERP, WMS, TMS, IoT) with optimized SQL and Python scripting.
- Apply data warehousing concepts (star/snowflake schemas), data validation, cleansing, and transformation techniques.
- Implement version control and CI/CD for data products, ensuring high performance and reliability.
- Leverage cloud platforms (Azure, AWS, GCP) and strong debugging, problem-solving, and communication skills to support supply chain analytics and reusable data pipelines.
Desired Skills:
- Data Engineer
- SQL
- Python
- azure