Data Engineer

OCBC; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive salary package

Learning & development opportunities

Enterprise-scale data & AI initiatives

Collaborative culture

Job summary

OCBC, Singapore’s longest‑established bank, seeks a Data Engineer (AVP) to build and refine data pipelines powering an enterprise data warehouse and AI knowledge base. You will work with senior engineers and leaders to transform structured and unstructured data into reliable datasets supporting risk, customer engagement, fraud detection, and intelligent automation.

The role offers hands-on data engineering with growth into streaming, real‑time, and AI-driven data products within a banking

Qualifications

• 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.
• Hands-on experience with modern data architectures (DW, lakehouse) and batch/real-time processing.
• Experience with AI knowledge bases, vector databases, embeddings and semantic search is a plus.
• Experience with LLM/AI agent use cases is a plus.

Responsibilities

• Build and maintain data pipelines feeding data warehouse/lakehouse platforms (Cloudera, Redshift, BigQuery).
• Develop data models for reusable analytical datasets and reporting foundations.
• Create and maintain batch processing jobs using SQL, Spark, Python/Java.
• Support real-time streaming pipelines with Flink, Kinesis or similar.
• Build/operate CDC pipelines (Debezium, Confluent, Fivetran).
• Ingest data from APIs, GA4 and other sources; implement Pub/Sub/Kafka integrations.
• Develop Airflow or Dagster workflows for scheduled/event-driven tasks.
• Assist in building REST APIs and backend services with Python/Flask.

Skills

Data engineering

Data pipelines

Cloud architecture

Python

SQL

ETL

Streaming

Airflow

Education

Bachelor’s degree in Computer Science

Master’s degree in Computer Science

Tools

Cloudera

BigQuery

Redshift

Spark

Kafka

Flink

Pub/Sub

Terraform

Job description

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 (Assistant Vice President) 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.

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
• Develop and maintain batch data processing jobs using SQL, Spark, dbt, Python or Java
• Support and contribute to real‑time streaming pipelines using Flink, AWS Kinesis or similar tools
• 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
• Follow established SLAs and monitoring practices, and help troubleshoot pipeline issues

Orchestration & Automation

• Develop and maintain Airflow DAGs or Dagster 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 pipelinesBuild, 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 stakeholders (Risk, Marketing, Operations)
• Help translate business requirements into technical implementation tasks
• Participate in code reviews and contribute to a culture of continuous improvement

REQUIREMENTS

• 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.
• Solid hands‑on experience in build data pipelines on modern data architectures including Data Warehouse, Lakehouse, and batch/real-time data processing systems.
• Working AI knowledge base concepts: vector databases, embeddings, and semantic search is a plus
• Hands‑on RAG pipeline components such as document chunking, embedding generation, and retrieval is a plus
• Good experience on building data layers that support LLM / AI agent use cases is a plus.
• Experience in banking or financial services is a plus

Technical Stack

• Data Warehouse / Platform: exposure to Cloudera, BigQuery, Redshift, or similar
• Batch Processing: Spark, SQL, ETL, Python, Map/Reduce
• Streaming: Familiarity with Flink or other real‑time processing engines
• CDC: exposure to Debezium, Confluent, Fivetran, or similar (Good to have)
• Data Ingestion: APIs, GA4, Pub/Sub, Kafka, Python pipelines
• Orchestration: Airflow, Dagster or equivalents
• Cloud & Infrastructure: GCP or AWS; basic Docker/Kubernetes/Cloud Run experience
• DevOps / DataOps: exposure to CI/CD pipelines and Terraform
• Backend & Serving: Python, Flask, REST APIs; familiarity with Redis a plus

Additional Preferred Experience

• Eagerness to learn real‑time / streaming architectures and low‑latency system design
• Basic exposure to LLM applications, RAG, or AI agent concepts is a plus, not required
• Good product mindset and willingness to treat data as a product, not just a project
• Strong communication skills and comfort collaborating with both technical and business stakeholders

WHAT WE OFFER

• Competitive base salary and comprehensive benefits.
• Strong learning and development opportunities.
• Exposure to impactful, enterprise‑scale Data and AI initiatives across the OCBC Group.
• A collaborative environment that values innovation, craftsmanship, and continuous improvement.
• Your wellbeing, growth, and aspirations matter to us as much as delivering value to our customers.

What We Offer:

Competitive base salary. A suite of holistic, flexible benefits to suit every lifestyle. Community initiatives. Industry-leading learning and professional development opportunities. Your wellbeing, growth and aspirations are every bit as cared for as the needs of our customers.