Data Engineer (Assistant Vice President)

About the role

OCBC is looking for a Data Engineer (Assistant Vice President) to build, maintain and improve data pipelines that power an enterprise-grade data warehouse and an AI knowledge base in a banking environment. Working closely with senior engineers and the head of data engineering, you will turn structured and unstructured data into reliable datasets and services supporting risk management, customer engagement, fraud detection and intelligent automation. This is a hands-on engineering role with opportunities to move into streaming, real-time and AI-driven data products.

Key responsibilities

• Build and maintain batch and streaming pipelines feeding data warehouse and lakehouse platforms (Cloudera, AWS Redshift, GCP BigQuery)
• Develop data models and batch jobs using SQL, Spark, dbt, Python or Java, and support real-time streaming with Flink, AWS Kinesis or similar
• Help build CDC pipelines (Debezium, Confluent, Fivetran), ingestion pipelines from APIs and GA4, and messaging integrations with Pub/Sub and Kafka
• Develop Airflow DAGs or Dagster, deploy workloads on Cloudera, GCP or AWS, and maintain CI/CD pipelines
• Provision infrastructure with Terraform, build REST APIs and backend services with Python/Flask, and use Redis caching
• Support vector database pipelines, embedding generation, document chunking and semantic search for AI knowledge bases and RAG pipelines
• Collaborate with senior engineers, AI teams and business stakeholders, and take part in code reviews

Required profile

• Diploma, Bachelor's or Master's degree in computer science or a related field
• At least 5 years of experience in data engineering, data platforms or related roles
• Experience building data pipelines on modern architectures (data warehouse, lakehouse, batch and real-time processing)
• Experience in banking or financial services is a plus

Required skills

• Data warehouse and platform: Cloudera, BigQuery, Redshift or similar
• Batch processing: Spark, SQL, ETL, Python, Map/Reduce
• Streaming: Flink or other real-time engines
• CDC and ingestion: Debezium, Confluent, Fivetran, Kafka, Pub/Sub, Python pipelines
• Orchestration: Airflow, Dagster or equivalents
• Cloud and DevOps: GCP or AWS, Docker, Kubernetes, Cloud Run, CI/CD, Terraform
• Backend: Python, Flask, REST APIs; Redis a plus
• Preferred: vector databases, embeddings, semantic search, RAG, LLM/AI agent use cases

What we offer

• Competitive base salary and a suite of flexible benefits
• Learning and development opportunities
• Exposure to enterprise-scale data and AI initiatives across the OCBC Group
• A collaborative environment that values innovation and craftsmanship