AVP, Data Engineer (Information Security & Digital Risk Management)

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

Job summary

OCBC Bank in Singapore is seeking an experienced Data Engineer to build secure, production-grade data pipelines and analytics solutions for information risk monitoring. You will transform structured and unstructured data into trusted datasets and collaborate with risk, business and technology stakeholders in a regulated banking environment.

Bring 6+ years of hands-on data engineering experience, strong SQL, Python, Spark and Hadoop skills, and a mindset of secure-by-design.

Qualifications

• 6+ years of hands-on data engineering experience.
• Experience with large-scale distributed data platforms and data warehousing.
• Background in risk management is advantageous.
• Proficient with Teradata/Oracle, SQL, and PL/SQL.
• Familiar with Hadoop ecosystem: Hadoop, Spark, Hive, Impala, HDFS, HBase, Scala.
• Experience with DBT and managing structured/unstructured data.

Responsibilities

• Develop and enhance data pipelines and system architecture.
• Enable ingestion from structured and unstructured sources via Talend.
• Translate business requirements into data models and pipeline designs.
• Support SIT, UAT, OAT and production verification.
• Maintain data lineage and operational documentation.
• Embed secure-by-design and data governance practices.

Skills

SQL

Python

Spark

Hadoop

Talend

DBT

Data modeling

Tools

Teradata

Oracle

HIVE

Impala

HDFS

Scala

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.

Why Join

Join OCBC's Group Information Security & Digital Risk Management team and contribute directly to strengthening the Bank's information risk monitoring, analytics and control capabilities. This full-time Data Engineer role is hands‑on and delivery-focused: you will build secure, reliable data pipelines and data products that enable actionable risk insights across the Group.

You will work with business, risk and technology stakeholders to transform structured and unstructured data into trusted, production‑grade datasets and analytics solutions, while applying sound engineering practices in a regulated banking environment.

How You Succeed

You succeed by being a hands‑on data engineering practitioner who can independently translate business and information risk requirements into robust, production‑grade data engineering solutions.

Success in this role requires:

• Build and maintain scalable ETL/ELT pipelines for batch and near-real-time data ingestion, transformation and delivery.
• Apply strong SQL, Python, Spark, Hadoop and data modelling skills to solve practical information risk and analytics problems.
• Use orchestration, scheduling and monitoring tools to ensure pipeline reliability, operational resilience and timely issue resolution.
• Collaborate clearly with risk, business, technology, production support and platform teams across requirements, UAT, deployment and warranty support.

What You Do

Data Engineering Delivery

Responsible for developing and enhancing data pipelines and system architecture.

Create and maintain the optimal data pipeline to enable ingestion from a wide variety of structured and unstructured data sources via Talend.

Define and understand business requirements to develop and implement solutions.

Support development and deployment of applications utilising the data pipelines to provide actionable insights.

Involve in UAT execution with a focus on strategic testing processes and procedures to ensure that business standards and specifications are met.

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery and cleansing/transformation.

Collaborate with multiple stakeholders independently to drive key initiatives and projects.

Solutioning, Testing & Production Support

Translate business and information risk requirements into technical specifications, data models, pipeline design and implementation plans.

Support SIT, UAT, OAT and production verification, ensuring business standards, acceptance criteria and control expectations are met.

Own technical delivery through deployment, production onboarding, warranty support and issue resolution.

Maintain documentation for data lineage, transformation rules, operational procedures and support handover.

Information Security & Digital Risk Management

Support data-driven information risk initiatives, including staff abnormal activity monitoring, control analytics, risk indicators and management dashboards.

Embed secure‑by‑design and data governance practices into pipeline development, including access control, data handling, auditability and monitoring considerations.

Contribute to risk governance, control enhancements and regulatory‑aligned reporting through reliable data engineering outputs.

Help convert information risk use cases into repeatable analytics assets, reusable data marts and sustainable operating processes.

Who You Are

Experience

Minimum 6 years of hands‑on experience in data engineering, large-scale distributed data platforms, data warehousing, and analytics engineering.

Experience in risk management and project management will be advantageous.

Technical Skills

Strong background in traditional structured database environments such as Teradata / Oracle, SQL and PL/SQL.

Fluent in the management of structured and unstructured data, as well as modern data transformation methodologies and tools such as DBT.

Proficient in Hadoop ecosystem components, including HIVE, Impala, HDFS, Spark, Scala and HBase.