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Data Engineer

Data Engineer - January 1, 2023

Job Descriptions

  • Collaborate with BI Solution Architect and Business Analyst to convert requirements into technical specifications
  • Establish both batch and real-time data pipelines, primarily using Kafka-Spark Streaming for ETL processes
  • Transfer data from multiple sources to a centralized area for data scientists, engaging in discussions with data scientists to determine the preferred data format
  • Move modeling results to the target front-end application, consulting with Business Units and Business Analysts for specific requirements
  • Generally, load data into a database or designated storage; in rare cases, develop REST API services for front-end applications to access real-time data
  • Document source-target mappings within the created pipelines
  • Maintain and monitor data pipelines to ensure correct, available, and restricted access to authorized personnel
  • Adhere to the SCB SDLC process by collaborating with various teams, including Architects, IT security, Quality Assurance, and Change


  • Preferred academic background: BSc or MSc in computer science, software engineering, or information technology
  • Proficient in Spark, SQL, Python, or Scala
  • Experience in software development life cycles: coding, unit testing, using git or other SCM, CI/CD pipelines, and monitoring logs or service resource usage
  • Fundamental knowledge in computer engineering: systems, networks, and security
  • Strong communication and interpersonal skills to collaborate effectively with both technical teams (scientists/engineers) and non-technical business units
  • Preferred Qualifications

  • Prior work experience in roles such as ML Engineer, Data Engineer, Fullstack or Backend Software Engineer, Solution/Cloud Architect, or related positions.
  • Experience with Kubernetes, Kafka, Hadoop, Hive, and sFTP
  • Experience with cloud platforms, with a preference for Azure: Azure Storage, Azure Data Factory, and Databricks
  • Experience in developing data warehouse, big data, and business intelligence applications, particularly in a competitive service industry, preferably in banking, financial services, or telecom
  • Have data privacy and PDPA awareness
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