Data Engineer (AVP)

Posted 4 Days Ago
Be an Early Applicant
Hiring Remotely in Office, Machaze, Manica, MOZ
Remote
Senior level
Financial Services
The Role
Build and maintain enterprise data pipelines, warehouse and lakehouse datasets, batch and streaming systems, CDC integrations, Airflow workflows, cloud infrastructure, APIs, and AI knowledge-base pipelines. Develop reliable data services supporting risk, customer engagement, fraud detection, and automation. Collaborate with engineering, AI, and business teams while contributing to monitoring, troubleshooting, code reviews, CI/CD, and continuous improvement.
Summary Generated by Built In
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 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 (Good to have)

  • CDC: exposure to Debezium, Confluent, Fivetran, or similar (Good to have)

  • Data Ingestion: APIs, GA4, Pub/Sub, Kafka, Python pipelines

  • Orchestration: Airflow 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.

Skills Required

  • Diploma, bachelor's degree, 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 building data pipelines on data warehouse, lakehouse, batch-processing, and real-time data architectures
  • Experience with data engineering technologies such as Spark, SQL, Python, ETL, and data ingestion pipelines
  • Experience with data warehouse or platform technologies such as Cloudera, BigQuery, Redshift, or similar
  • Experience with Airflow or equivalent workflow orchestration tools
  • Experience with GCP or AWS and basic Docker, Kubernetes, or Cloud Run
  • Exposure to CI/CD pipelines and Terraform
  • Experience with Python, Flask, REST APIs, and backend data services
  • Working knowledge of vector databases, embeddings, and semantic search
  • Hands-on experience with RAG pipeline components including document chunking, embedding generation, and retrieval
  • Experience building data layers for LLM or AI agent use cases
  • Experience in banking or financial services
  • Familiarity with Flink or other real-time processing engines
  • Exposure to Debezium, Confluent, Fivetran, or similar CDC tools
  • Familiarity with Redis
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The Company
HQ: Singapore
Year Founded: 1932

What We Do

OCBC is the longest established Singapore bank, formed in 1932 from the merger of three local banks, the oldest of which was founded in 1912. It is now the second largest financial services group in Southeast Asia by assets and one of the world’s most highly-rated banks, with an Aa1 rating from Moody’s. Recognised for its financial strength and stability, OCBC is consistently ranked among the World’s Top 50 Safest Banks by Global Finance and has been named Best Managed Bank in Singapore by The Asian Banker. OCBC and its subsidiaries offer a broad array of commercial banking, specialist financial and wealth management services, ranging from consumer, corporate, investment, private and transaction banking to treasury, insurance, asset management and stockbroking services. OCBC’s key markets are Singapore, Malaysia, Indonesia and Greater China. It has more than 570 branches and representative offices in 19 countries and regions. These include about 300 branches and offices in Indonesia under subsidiary Bank OCBC NISP, and over 90 branches and offices in Mainland China, Hong Kong SAR and Macau SAR under OCBC Wing Hang. OCBC’s private banking services are provided by its wholly-owned subsidiary Bank of Singapore, which operates on a unique open-architecture product platform to source for the best-in-class products to meet its clients’ goals. OCBC's insurance subsidiary, Great Eastern Holdings, is the oldest and most established life insurance group in Singapore and Malaysia. Its asset management subsidiary, Lion Global Investors, is one of the largest private sector asset management companies in Southeast Asia.

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