AVP, AI Data Engineer (Data Loss Monitoring)

About Ocbc

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.
• Or simply enjoy a vibrant, future-ready career.
• Your Opportunity Starts Here.
• Why join Join OCBC’s Data Loss Monitoring (DLM) team to modernise monitoring through AI, automation, data engineering and analytics.
• You will develop secure, reliable and scalable solutions that strengthen detection, alert review, investigation, oversight and management reporting in a regulated banking environment.
• How you succeed Deliver AI, automation, data and programming solutions from concept through deployment and production support.
• Translate DLM control requirements and risk scenarios into practical workflows, data products and analytics.

Responsibilities

• Apply secure-by-design engineering, sound governance and disciplined delivery practices.
• DLM domain knowledge and apply it to strengthen monitoring and investigation capabilities.
• What you do AI, Automation & Programming Design and deploy AI-assisted solutions, agents and workflows for DLM alert triage, investigation, case enrichment, escalation and reporting.
• Automate manual DLM processes using Python, APIs, workflow orchestration and scripting.
• Develop prototypes and production-ready applications for structured and unstructured data, including large or complex files and text.
• Assess AI and automation use cases for accuracy, explainability, human oversight, control impact and operational resilience.
• Simplify DLM processes and reduce manual effort without weakening control quality.
• Data Engineering & Analytics Design and maintain scalable ETL/ELT pipelines to ingest, transform and deliver DLM monitoring data for analytics, investigations, automation and AI use cases.
• Integrate structured and unstructured sources into trusted datasets, reusable data marts, dashboards and risk analytics.
• Use SQL, Python and data engineering frameworks for cleansing, transformation, reconciliation, quality validation and performance optimisation.
• Implement scheduling, orchestration, monitoring, logging and exception handling for reliable production operations.
• Document data lineage, transformation rules, technical designs and operational procedures.
• Data Loss Monitoring & Detection Enablement Develop practical knowledge of DLM policies, alert generation, analyst review, investigation, escalation and management reporting.
• Translate DLM control requirements, analyst needs and risk scenarios into sustainable technical capabilities and operating processes.
• Enhance content inspection and detection using regex, pattern matching, Exact Data Matching, fingerprinting, classification and contextual analytics.
• Use data and analytics to identify trends, control gaps, abnormal activity and opportunities to improve risk-based monitoring.
• DLM transformation initiatives, including AI-assisted reviews and intelligent automation, risk-based monitoring and future-state operating capabilities.
• Deliver DLM transformation initiatives, including AI-assisted reviews and intelligent automation, risk-based monitoring and future-state operating capabilities.
• Solution Delivery, Governance & Stakeholder Management Convert DLM requirements into technical specifications, solution designs, data models, implementation plans and acceptance criteria.
• Support SIT, UAT, OAT, deployment, production verification, onboarding, warranty support and issue resolution.
• Partner with Technology, Data, Information Security, Compliance, Operational Risk, Internal Audit and Business Units.
• Ensure compliance with technology risk, information security, privacy, data governance, model risk and Responsible AI requirements.
• Provide clear progress updates, recommendations and risk considerations to management and governance forums.
• Who you are A hands-on AVP with strong programming and solution-delivery experience who can serve as the DLM team’s AI, automation and data engineering specialist.
• The candidate is motivated to build DLM domain knowledge and apply modern technology to strengthen monitoring, investigation and control capabilities.

Requirements

• Build trusted pipelines and AI-assisted tools that improve triage, investigation, reporting and control effectiveness.
• Degree in Computer Science, Data Science, Information Security, Engineering or a related discipline.
• Typically 6+ years of hands-on experience in AI engineering, automation, software development, data engineering, analytics engineering or related roles.
• Experience delivering solutions end-to-end, including requirements, design, development, testing, deployment and production support.
• Strong Python and SQL, with experience in APIs, scripting, automation frameworks and sound software-engineering practices.
• Knowledge of AI/ML or LLM patterns, including prompt engineering, retrieval-augmented generation, agentic workflows, model integration, evaluation and human-in-the-loop controls.
• Working knowledge of secure coding, access control, encryption, audit logging, data quality, lineage and production monitoring.
• Knowledge of DLP platforms, content inspection, regex-based detection or data classification is advantageous.
• Hands-on technical leader who is comfortable designing, coding, troubleshooting and reviewing implementation details.
• Strong analytical judgement on when to use AI, automation, data engineering or simpler rule-based approaches.
• Able to translate operational and control needs and explain technical topics clearly to diverse stakeholders.
• Strong ownership, delivery discipline and attention to detail in a production control environment.
• Curious, collaborative and able to build DLM expertise while independently driving deliverables end-to-end.

Preferred

• Experience working across business, risk and technology teams; banking or another regulated environment is preferred.
• DLP, cyber-security monitoring or information-risk experience is advantageous, but not mandatory.

Benefits

• Build lasting value in your community.
• Help people grow their assets, business, and investments.
• Take your learning as far as you can.
• 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.