Data Engineer jobs in Singapore

The Data Science and Tools Development team is at the forefront of AI Transformation within Seagate's Product Development Group. Our mission is to leverage AI and Machine Learning technologies to accelerate product development, ensuring that we meet production volume and reliability standards. By utilizing AI/ML, we enhance our research capabilities and drive continuous innovation.

We are seeking a highly skilled and versatile Full Stack Data Engineer to join our dynamic team. The ideal candidate will have a strong background in both data engineering and software development, with the ability to design, build, and maintain end-to-end data solutions. As a Full Stack Data Engineer, you will work closely with cross-functional teams to ensure seamless data integration, processing, and analysis, driving business growth and innovation.

• Design, develop, and maintain robust data pipelines to ensure efficient data flow and integration across various systems.
• Build and optimize data storage solutions, including data warehouses and data lakes.
• Develop and maintain APIs and microservices to support data access and integration.
• Implement data processing and transformation workflows using ETL tools and frameworks.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver actionable insights.
• Ensure data quality, integrity, and security through rigorous testing and validation processes.
• Monitor and troubleshoot data pipelines and systems to ensure optimal performance and reliability.
• Stay up-to-date with the latest advancements in data engineering, software development, and related technologies.

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
• 3+ years of experience in data engineering, software development, or a related field.

• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with SQL and NoSQL databases, including data modeling and query optimization.
• Familiarity with big data technologies such as Apache Hadoop, Spark, and Kafka.
• Knowledge of cloud platforms like AWS, Google Cloud Platform, or Azure.
• Experience with data integration tools (e.g., Apache NiFi, Talend) and ETL frameworks.
• Strong understanding of data architecture, data warehousing, and data governance principles.
• Excellent problem-solving skills and the ability to work collaboratively in a team environment.
• Strong communication and presentation skills, with the ability to convey complex concepts to diverse audiences.