Experience:

5 years required

Skills:

Architecture, Leadership Skill, Big Data, Python, English

Job type:

Full-time

• Architect and optimize high-throughput data pipelines and unstructured data processing frameworks to directly power the enterprise AI Foundation Platform.
• Co-own the vector infrastructure alongside the AI Engineer Specialist, ensuring optimized embedding storage, indexing strategies, and fast vector search retrieval.
• Build automated ETL/ELT pipelines capable of transforming raw enterprise data into AI-ready formats (chunking, metadata tagging, and cleaning).
• Data Governance, Metadata & Cataloging.
• Implement metadata pipelines for comprehensive data catalog and data dictionary services, including schema capture, lineage tracking, and audit logging.
• Enforce data governance, access controls, and privacy compliance across all data stores used for training, fine-tuning, and RAG retrieval.
• Design and maintain operational data lineage to ensure transparency and auditability of data flowing into production AI models.
• Advanced AI Component Integration.
• Develop and tune robust data ingestion pipelines for OCR, NLP processing, recommendation systems, and multi-modal AI inputs.
• Optimize data tiering and caching strategies to reduce latency and infrastructure costs for live enterprise AI workloads.
• Build secure, scalable data connectors linking legacy enterprise databases with modern LLM frameworks and autonomous agents.
• Collaboration & Data Excellence.
• Partner directly with the AI Engineer Specialist to ensure seamless data delivery for real-world, high-concurrency production deployments.
• Bridge traditional data engineering practices with modern MLOps, setting up automated data validation, quality checking, and drift detection at the data layer.
• Provide data-level expertise during architecture reviews, ensuring scalable data design patterns across the entire AI project lifecycle.
• Key Impacts.
• Ensure high-quality, AI-ready data ingestion at scale, dramatically reducing the time-to-market for enterprise AI assets.
• Establish a secure and compliant data foundation that guarantees enterprise data privacy during AI model interactions.
• Eliminate data bottlenecks in real-world production environments, ensuring sub-second latency for enterprise RAG and search systems.
• Transition traditional data warehouses and lakes into future-ready, graph- and vector-enabled AI data infrastructure.
• Master's or Bachelor's degree in Computer Engineering, Computer Science, Data Engineering, or a related technical field.
• 5+ years of experience in heavy-duty Data Engineering, Big Data, or Distributed Systems, with strong production experience in an AI/ML context.
• Proven track record of building large-scale data infrastructure supporting live, mission-critical applications.
• Technical & AI Data Framework Expertise.
• Deep experience in Python and SQL, alongside modern big data tools (e.g., Spark, Kafka, or cloud equivalents).
• Hands-on expertise in Vector Databases and unstructured data processing.
• Strong understanding of data chunking strategies, text extraction (OCR/NLP pipelines), and metadata orchestration.
• Familiarity with cloud data platforms (AWS/Azure/GCP) including managed data lakes, data warehouses, and cloud-native security/encryption.
• Real-world experience implementing data catalogs, schema evolution, and automated data quality monitoring.
• Leadership & Soft Skills.
• Excellent technical communication skills to align data pipeline designs with AI model engineering requirements.
• Strong analytical and problem-solving mindset, comfortable handling noisy, unstructured enterprise data under tight deadlines.
• Good verbal and written English communication skills for vendor engagement and cross-functional team collaboration.

Experience:

5 years required

Skills:

Good Communication Skills, Microsoft Office, Internal Audit, Data Analysis, Power point

Job type:

Full-time

• Special Projects and Process Improvement.
• Design and implement automation (RPA / system enhancement) to reduce manual work, error rate, and turnaround time.
• Be able to initiate transformation of premium collection processes across all payment channels (digital, transfer, cheque, bank deduction).
• Partner with IT, PMO, and vendors to deliver transformation projects.
• Redesign collection and reconciliation processes with embedded controls and audit readiness.
• Establish standardized SOPs, control checkpoints, and escalation mechanisms.
• Ensure alignment with Group policies, OIC requirements, and internal audit expectations.
• Premium Collection Operations Execution & Control.
• Ensure end to end accuracy of premium collection processes for both new and renewal business, including AML screening, premium posting in the core system (AS400), and preparation of premium receipt reports for accounting.
• Review and validate premium collection transactions to confirm completeness, accuracy, and compliance with company policies, standard operating procedures, and regulatory requirements.
• Monitor and control each stage of the collection workflow to ensure disciplined execution, adherence to internal control standards, and timely identification and escalation of errors or exceptions.
• Coordinate closely with the Collection colleague and related team to maintain smooth daily operations, provide technical guidance on issue resolution, and ensure consistent process application across all cases.
• Payment Method coming from.
• Digital Payment Method (Gen Pay).
• Transfer (Sale Channels, Call Center).
• Cheque / - Customer Walk-in.
• Billing Notification Letter.
• Bank Deduction (Renewal - Recurring Payment).
• Premium Reconciliation and Control Management.
• Reconcile premium collections, bank statements, and related charges to ensure accuracy, completeness, and timely closure.
• Review and validate reconciliation results in a checker capacity, ensuring compliance with internal control standards and audit requirements.
• Investigate, analyze, and resolve reconciliation discrepancies within defined SLA.
• Drive continuous improvement by identifying control gaps, streamlining reconciliation workflows, and supporting automation initiatives.
• Refund Premium Collection to customers.
• Execute the premium refund process by coordinating with banks and internal stakeholders, including POS and Accounting.
• Ensure timely and accurate updates of refund transactions in the premium reconciliation records for accounting purposes.
• Liaise with banks to resolve refund issues or delays promptly, ensuring smooth resolution and a positive customer experience.
• Bachelor's degree in business administration, Finance and Accounting, or related fields.
• Minimum 5 years of experience in premium collection, insurance operations, or financial transaction processing. Experience working with AS400 is preferable.
• Strong exposure to process transformation, automation, or operational excellence initiatives.
• Solid understanding of end to end premium collection, reconciliation, accounting interface, and controls Stakeholder Management: Coordinate with other departments and external partners.
• Strong ownership mindset with a proactive, "can-do" attitude and ability to drive results under pressure.
• Good team player with service minded and self-development ability.
• Attention to details and good communication skills.
• Intermediate Level in English both written and spoken.
• Proficient in Microsoft Office applications, particularly MS Excel (e.g., data analysis, reconciliation tracking), PowerPoint, and Word.