WHO WE ARE: As Singapore’s longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires. Today, we’re on a journey of transformation. Leveraging technology and creativity to become a future-ready learning organisation.
But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia’s leading financial services partner for a sustainable future. We invite you to build the bank of the future. Innovate the way we deliver financial services. Work in friendly, supportive teams. Build lasting value in your community. Help people grow their assets, business, and investments. Take your learning as far as you can.
Or simply enjoy a vibrant, future-ready career. Your Opportunity Starts Here. WHO WE ARE As Singapore’s longest‑established bank, OCBC has supported individuals and businesses in achieving their aspirations since 1932. We are transforming into a future‑ready learning organization – leveraging technology and innovation while staying true to our ambition to be Asia’s leading financial services partner for a sustainable future.
Join us to build the bank of the future, work in collaborative teams, and create lasting value for our customers and communities. ROLE We are seeking a Data Engineer (AVP) to build, maintain, and continuously improve data pipelines that power enterprise‑grade data warehouse, AI knowledge base within a banking environment. Working closely with senior engineers and the head of data engineering, you will help transform structured and unstructured data into reliable, reusable datasets and services that support use cases such as risk management, customer engagement, fraud detection, and intelligent automation.
This is a hands‑on engineering role with strong opportunities to grow into streaming, real‑time, and AI‑driven data product work. This role reports to VP/ED, Data Engineering, Group data office. KEY RESPONSIBILITIES Batch & Streaming Data Pipeline Development Build and maintain data pipelines feeding data warehouse / lakehouse platforms (e.g., Cloudera, AWS Redshift or GCP BigQuery) Implement data models to support reusable analytical datasets and reporting foundations Follow established SLAs and monitoring practices, and help troubleshoot pipeline issues Develop and maintain batch data processing jobs using Spark, SQL, Python or Java Support and contribute to real‑time streaming pipelines using Flink or similar tools, under senior guidance Assist in building and operating CDC pipelines (e.g., Debezium, Confluent or Fivetran) Build and maintain ingestion pipelines from APIs, GA4, and other data sources Implement messaging/streaming integrations using Pub/Sub and Kafka Write clean, well‑tested SQL and Python scripts and data ingestion and processing pipelines Orchestration & Automation Develop and maintain Airflow DAGs for scheduled and event‑driven workflows Follow orchestration best practices established by senior engineers Cloud Infrastructure & DevOps Deploy and support data workloads on Cloudera, GCP (Docker, Kubernetes, Cloud Run), AWS equivalent Contribute to and maintain CI/CD pipelines Use Terraform to provision and manage infrastructure under senior guidance Build and support REST APIs and backend services using Python / Flask Use Redis caching to meet performance requirements for data services AI Knowledge Base & RAG Support Assist in building and maintaining vector database pipelines and embedding generation jobs under senior guidance Support to deliver processing and chunking workflows that feed AI knowledge bases and RAG pipelines Build, test and monitor semantic search / retrieval quality for AI‑facing data layers Cross‑functional Collaboration Work closely with senior data engineers, AI teams, and business