เงื่อนไขการค้นหา

ทักษะ:

ETL

ประเภทงาน:

งานประจำ

• Design and deliver cloud-native banking solutions on AWS.
• Build rapid prototypes and live demos for client engagements.
• Integrate AI and data capabilities into core banking platforms.
• The ideal candidate combines strong engineering depth, banking domain expertise, and the ability to translate ideas into working solutions quickly.
• Core Banking Transformation.
• Lending / loan origination and servicing.
• Credit decisioning systems.
• Payments, deposits, and investment platforms.
• Legacy cloud-native (rehost, replatform, refactor).
• Monolith microservices / event-driven architecture.
• Translate business requirements into scalable, secure, production-ready architectures.
• Client-Facing Demo & Prototyping (Critical Requirement).
• Build end-to-end functional prototypes and demos on AWS to showcase solutions.
• Working applications.
• API-driven services.
• AI/data-driven proof-of-value solutions.
• Solution workshops.
• Pre-sales discussions.
• Live demo sessions with business and technology stakeholders.
• Expected capability: Build a working demo (e.g., AI-powered credit workflow or customer 360 solution) within short timelines.
• AWS Cloud Engineering (Hands-on Senior Level).
• Architecture & Design.
• Microservices and event-driven patterns.
• API-first integration models.
• High availability, scalability, and resiliency.
• Security and regulatory compliance.
• Core AWS Stack.
• Compute: Lambda, ECS/EKS, EC2.
• Data: S3, Aurora/RDS, DynamoDB.
• Integration: API Gateway, Step Functions, EventBridge.
• Observability: CloudWatch and monitoring frameworks.
• DevOps & Automation.
• Infrastructure-as-Code (Terraform / CloudFormation / CDK).
• CI/CD pipelines and automated deployment.
• Ability to stand up environments quickly for demos and delivery.
• AI & Data Capabilities in Banking (Strong Preference).
• Data Engineering.
• Data lakes (S3-based architectures).
• ETL / ELT pipelines.
• Customer, transaction, credit, and risk datasets.
• Machine Learning & Analytics.
• Credit scoring and underwriting.
• Fraud detection / AML.
• Customer segmentation and personalization.
• GenAI & Modern AI.
• RAG-based solutions (e.g., document processing, KYC).
• AI assistants for banking users.
• AWS Bedrock / SageMaker / equivalent.
• LLM orchestration and vector search.
• Real-Time Decisioning.
• Real-time credit approvals.
• Fraud detection and alerts.
• Client Engagement & Thought Leadership.
• Act as a trusted technical advisor to financial services clients.
• Architecture discussions.
• Solution design workshops.
• Pre-sales and technical solutioning.
• Core banking modernization.
• Cloud + AI transformation.
• Bridge business, data, and technology stakeholders effectively.
• Banking technology / financial services IT.
• Core banking systems (lending, payments, deposits, investments).
• Core banking modernization or migration programs.
• Large-scale transformation initiatives.
• Cloud-native architecture and development.
• Microservices / distributed systems.
• Strong hands-on programming experience in Python (preferred), with the ability to build cloud-native applications, data pipelines, and rapid client-facing prototypes.
• Build working demos / PoCs under time pressure.
• Operate effectively in client-facing roles..
• Preferred Qualifications.
• Temenos, Mambu, Finacle, FLEXCUBE, nCino.
• Data engineering and analytics platforms.
• ML / GenAI use cases integrated into business workflows.
• Event-driven architecture.
• API-first ecosystems.
• Domain-driven design (DDD).
• AWS Certifications (Associate / Professional).
• Profile We Are Targeting.
• Hands-on builder (not a pure architect or program manager).
• Able to design, build, and demo solutions live to clients.
• Strong banking domain credibility.
• Bridges cloud + core banking + AI/data.
• Comfortable in pre-sales + delivery hybrid environments..