Vice President, Data Engineering

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 Imagine having the opportunity to build and shape the data foundation that powers critical business decisions across the bank. As a Vice President, Data Engineering , you will lead the design and evolution of enterprise-scale data platforms, enabling advanced analytics, AI, regulatory reporting, and digital transformation initiatives. You will work closely with business stakeholders, architects, data scientists, and technology teams to deliver reliable, scalable, and secure data solutions that support the bank's strategic objectives. How You Succeed To succeed in this role, you will combine deep technical expertise with strong leadership capabilities to architect and deliver modern data platforms. You will drive the adoption of engineering best practices, establish scalable data pipelines, and ensure data is trustworthy, accessible, and governed across the organization. Success will be measured by your ability to build high-performing engineering teams, optimize platform performance, improve data quality and reliability, and enable faster delivery of business insights through robust data infrastructure. What you will be doing: Define and drive the strategic roadmap for the enterprise data platform, ensuring scalability, resilience, security, and operational excellence. Design, develop, and maintain large-scale batch and real-time data pipelines using modern data engineering frameworks and technologies. Lead the architecture and optimization of distributed data platforms, including Hadoop, Spark, Data Lake, and cloud-based data ecosystems. Establish and govern data engineering standards, including data quality, metadata management, lineage, observability, and platform monitoring. Partner with business, analytics, data science, and application teams to translate business requirements into scalable and reusable data solutions. Drive DataOps and platform automation initiatives, including CI/CD, infrastructure-as-code, automated testing, and release management. Optimize platform performance, cluster utilization, storage efficiency, and processing workloads to support growing business demands. Ensure compliance with enterprise security, risk, governance, and regulatory requirements across all data environments. Lead, mentor, and develop a high-performing team of data engineers, fostering a culture of innovation, accountability, and continuous improvement. Evaluate emerging technologies and propose enhancements that strengthen the bank's data capabilities and future-readiness. Who are we looking for: Bachelor's degree in Computer Science, Information Technology, Software Engineering, Data Engineering, or a related discipline. Minimum 8 years of experience in Data Engineering, Data Platform Engineering, or Big Data environments, including leadership or solution architecture responsibilities. Extensive experience designing and implementing enterprise-scale data platforms and data integration solutions. Strong hands-on expertise in the Hadoop ecosystem, including HDFS, YARN, Hive, HBase, Sqoop, and related technologies. Advanced knowledge of Apache Spark (Core, SQL, Structured Streaming) and distributed computing concepts. Proficiency in Python, Scala, Java, and advanced SQL for large-scale data processing and optimization. Experience working with modern data architecture patterns including Data Lakes, Lakehouse platforms, and cloud-native data services. Strong understanding of data modelling, data governance, metadata management, and data quality frameworks. Experience implementing DevOps/DataOps practices, CI/CD pipelines, containerization, and orchestration technologies. Excellent stakeholder management and communication skills, with the ability to influence both technical and business audiences. Proven track record of leading engineering teams and delivering complex data transformation initiatives in large organizations. Preferred Qualifications Experience in banking, financial services, or highly regulated industries. Exposure to cloud platforms such as Teradata, Azure, AWS, or Google Cloud. Knowledge of data governance, regulatory reporting, risk, compliance, and audit requirements. Experience supporting AI, machine learning, and advanced analytics workloads on enterprise data platforms. #LI-SL1 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.