Job Description

About Us
We are the "Group Data Office", OCBC centre of excellence for Data Engineering, Artificial Intelligence, and Machine Learning Engineering. We are responsible for creating and managing a data-driven culture within the bank, leveraging data at scale to deliver real, significant benefits for the organization.
Role and Responsibilities

• Based in the Group Data Office - Data Engineering team, your role will involve developing and deploying scalable, reliable, and fault-tolerant data pipelines. This includes batch processing using Trino, dbt, and Dagster, as well as real-time processing with Kafka, Flink, and YugabyteDB.
• Collaborate with business users to define and understand their requirements in order to develop and implement effective solutions.
• Contribute to the development of our enterprise feature store, improving data quality and feature reusability for data science models across the organization.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery and cleansing/transformation.
• Support various business functions by collaborating with multiple stakeholders - business, IT, and vendors independently.

• Bachelor\'s or Master\'s degree in Computer Science, Information Technology, or a related quantitative field.
• Minimum 4 to 6 years of experience working in Data Engineering, Big Data solutions, and analytics functions.
• Solid background in traditional structured database environments such as Teradata / Oracle, SQL & PL/SQL.
• Hands-on experience with Hadoop ecosystem components like HIVE, Impala, HDFS, and Spark.
• Basic programming skills in at least one of the following languages: Python, Java, C++, or Scala.
• Experience with modern data lake query engines such as Presto/Trino/Athena, BigQuery, or similar.
• Knowledge of modern data transformation tools like dbt.
• Understanding of real-time data pipelines and streaming applications using Kafka, Flink, or other similar tools.
• Exposure to low latency databases, such as Redis, YugabyteDB, or others would be beneficial.
• Curiosity and passion for the data engineering ecosystem, as well as a tendency to stay updated with the latest technology advancements in the field.
• Energetic personality with an innovative, self-starting spirit. Someone who likes to ask "why?"

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