1. Proven experience as a Data Engineer or a related role in data engineering (data platform experience’s preferred)
2. Proficiency in one or more programming languages for data processing (e.g., Python, Java, Scala).
3. Experience with ETL tools and data integration platforms (e.g., Apache Nifi, Talend, Apache Beam).
4. Knowledge of big data technologies (e.g., Hadoop, Spark, Hive) is a plus.
5. Acquire good communication, strong analytical, and problem-solving skills.
6. Experience in design of data platform in both cloud and on-premises technologies e.g. AWS, SAP BW (might be advantages)Other Requirements (For Requirement):
1. In charge of implementing and maintaining scalable data architecture to support continuing increases in data variation and data volume for all database and da platforms such as SQL database, Oracle and cloud-based platform.
2. Design and implement and maintain robust data processing pipeline to ensure that data is secured across business area through multiple data centers and cloud architecture.
3. In charge of managing the data and meta-data (definition of the data) that stores in a data platform either in a structure or unstructured way.
4. Engage in design and maintain data life cycle management.
5. Integrate data from multiple sources, including APIs, databases, and external data feeds, to provide a unified and holistic view of our data.
6. Collaborates with BI, data scientist, and project team to design the great functionality in the data service system to build and improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization.
7. Ensure the data access has been granted and available for supporting data analytic/ business requirements.Support the design and implementation of data management solutions, including documentation