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

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. • Hands-on experience working on real-time data and streaming applications using Kafka or other similar tools. • Hands-on experience in automation process, including building procedures, ETL and automated job scheduling using data integration tools such as Talend. Information Risk Knowledge • Good understanding of technology, information and data risk concepts. • Awareness of data security controls, including access control, encryption, data handling, auditability and data governance. • Familiarity with regulatory-aligned technology risk management, information security or operational risk reporting will be advantageous. Competencies • Hands-on, analytical and comfortable solving complex data problems independently. • Strong attention to detail, with a reliability mindset for production-grade delivery. • Able to communicate technical topics clearly to business, risk and technology stakeholders. • Collaborative team player…