Data Engineer (Mgr)

OCBC Group; Singapore; On-site; SGD 90,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Flexible benefits

Professional development

Community initiatives

Job summary

OCBC Singapore is seeking a Data Engineer Manager to design and maintain data pipelines for enterprise data warehouses and AI knowledge bases. You will transform structured and unstructured data into reliable datasets, support risk management, customer engagement, fraud detection, and enable intelligent automation.

The role involves hands-on work across cloud, streaming, and AI-enabled data engineering with collaboration across senior engineers and cross-functional teams.

Qualifications

• Bachelor’s degree in computer science, information systems, engineering, or related field.
• 2+ years in data engineering, data platforms, software engineering, or related roles.
• Hands-on experience building or supporting data pipelines using SQL and Python in a data warehouse, data lake, or cloud environment.
• Basic knowledge of AI knowledge base concepts, vector databases, embeddings, or semantic search is a plus.
• Exposure to RAG components like document chunking, embedding generation, or retrieval is a plus.

Responsibilities

• Develop and support batch and streaming data pipelines feeding lake/data warehouse platforms.
• Implement data models for reusable analytical datasets and reporting.
• Monitor pipelines against SLAs and troubleshoot data quality issues.
• Write clean, tested SQL and Python code for ingestion and processing.
• Develop and support Airflow DAGs for scheduled workflows.
• Support REST APIs and backend services using Python and Flask.
• Assist with implementing AI knowledge base pipelines and vector embeddings.
• Collaborate with Risk, Finance, Marketing, and Operations stakeholders.

Skills

SQL

Python

Spark

Java

Airflow

Flask

REST APIs

Kafka

Docker

Kubernetes

Education

Bachelor's degree

Tools

Cloudera

Redshift

Snowflake

Flink

Airflow

Job description

## Data Engineer (Mgr)Apply: Onsite: OCBC Singapore: Full time: Posted Today: JR00011450# **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.# **ROLE**We are seeking a Data Engineer (Manager) to support the development, maintenance, and improvement of data pipelines for enterprise data warehouse and AI knowledge base platforms within a banking environment. Working under the guidance of senior engineers, you will help transform structured and unstructured data into reliable, reusable datasets that support use cases such as risk management, customer engagement, fraud detection, and intelligent automation. This is a hands-on role with strong learning opportunities across cloud, streaming, and AI-enabled data engineering. This role reports to Executive Director, Data Engineering, Group Data Office. **KEY RESPONSIBILITIES****Batch & Streaming Data Pipeline Development*** Develop and support data pipelines feeding data lake/ data warehouse platforms, such as Cloudera, AWS Redshift, Snowflakes, under senior guidance.* Support the implementation of data models for reusable analytical datasets and reporting* Monitor data pipelines against established SLAs and assist in troubleshooting data quality and processing issues* Develop and maintain batch processing jobs using Spark, SQL, Python, or Java* Assist with real-time streaming pipelines using Flink or similar tools* Build and support ingestion pipelines from APIs, GA4, files, and other data sources* Support messaging and streaming integrations using Pub/Sub or Kafka* Write clean, tested, and maintainable SQL and Python code for data ingestion and processing **Orchestration & Automation*** Develop and support Airflow DAGs (or similar tools) for scheduled and event-driven workflows* Follow established orchestration, coding, and operational standards **Cloud Infrastructure & DevOps*** Support data workloads on Cloudera, or AWS, with exposure to Docker, Kubernetes ((or similar tools)), or Cloud Run* Use and support established CI/CD pipelines* Develop and support simple REST APIs and backend services using Python and Flask* Support Redis caching for data services where required **AI Knowledge Base & RAG Support*** Assist in developing vector database pipelines and embedding generation jobs* Support document processing and chunking workflows for AI knowledge bases and RAG pipelines* Help test and monitor semantic search and retrieval quality for AI-facing data layers* undefined **Cross‐functional Collaboration*** Work with senior data engineers, AI teams, and business stakeholders across Risk, Finance, Marketing, and Operations* Assist in translating business requirements into clear technical tasks* Participate in code reviews, testing, documentation, and continuous improvement activities **REQUIREMENTS*** Bachelor’s degree in computer science, information systems, engineering, or a related field* At least 2 years of relevant experience in data engineering, data platforms, software engineering, or related roles.* Hands-on experience building or supporting data pipelines using SQL and Python in a data warehouse, data lake, or cloud environment.* Basic knowledge of AI knowledge base concepts, such as vector databases, embeddings, or semantic search, is a plus* Exposure to RAG components, such as document chunking, embedding generation, or retrieval, is a plus* Exposure to data layers supporting LLM or AI agent use cases is a plus.* Experience or interest in banking and financial services is a plus **Technical Stack*** Data Warehouse / Platform: basic experience with Cloudera, Redshift, or similar platforms* Batch Processing: working knowledge of SQL and Python; exposure to Spark, ETL, or MapReduce* Streaming: exposure to Flink or another real-time processing engine is good to have* Orchestration: basic experience with Airflow or equivalent tools* Cloud & Infrastructure: exposure to GCP or AWS; basic knowledge of Docker, or Cloud Run* DevOps / DataOps: basic exposure to CI/CD* Backend & Serving: Python, Flask, and REST APIs; **Additional Preferred Experience*** Eagerness to learn data engineering, real-time streaming, cloud, and low-latency system design* Exposure to LLM applications, RAG, or AI agent concepts is welcome but not required* A quality-focused mindset and willingness to treat data as a reusable product* Good communication, teamwork, problem-solving, and willingness to learn# # # **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.