Total 2 job vacancies by Digiworld Technologies Pte. Ltd.

Job Objective:
Lead the planning and end-to-end delivery of customer’s platform initiatives by translating business requirements into effective technical solutions. Drive stakeholder engagement, risk management, and resource optimization to ensure timely and high-quality delivery of enterprise data lake and data warehouse solutions

Responsibilities:

• The Technical Delivery Manager will be responsible for planning and execution of rollout projects for EDAG Re-platform due to Hardware and software got obsoleted. 
• Requirements Analysis: Collaborate with business stakeholders to gather and analyse requirements, translating them into actionable project plans. 
• Technical Solution Delivery: Coordinate with technical teams to translate business requirements into technical solutions, ensuring alignment with the bank's strategic objectives.
• Stakeholder Engagement: Act as point of contact for stakeholders, providing regular updates on project progress, addressing concerns, and managing expectations effectively.
• Risk Management: Identify and mitigate project risks and issues proactively, developing contingency plans as necessary to minimize disruptions to project timelines and deliverables.
• Resource Allocation: Allocate resources effectively to support project activities, including assigning tasks, managing workloads, and optimizing team productivity.

Requirements:

• Technical Solution Delivery: Coordinate with technical teams to translate business requirements into technical solutions, ensuring alignment with the bank's strategic objectives.
• Stakeholder Engagement: Act as point of contact for stakeholders, providing regular updates on project progress, addressing concerns, and managing expectations effectively.
• Risk Management: Identify and mitigate project risks and issues proactively, developing contingency plans as necessary to minimize disruptions to project timelines and deliverables.
• Resource Allocation: Allocate resources effectively to support project activities, including assigning tasks, managing workloads, and optimizing team productivity.
• Demonstrated strong understanding and extensive hands-on experience across multiple enterprise-scale Data Lake and Data Warehouse initiatives.
• Collaborate with business stakeholders to gather and analyse requirements, translating them into actionable project plans.
  

Job Objective:

Analyze and translate business, regulatory, and analytics requirements into scalable data and solution designs. Drive effective stakeholder communication, effort estimation, and validation processes, while enabling data architectures and curation strategies that support reporting, analytics, and AI/NLP-driven use cases.

Responsibilities:

• Perform detailed effort estimation for projects and change requests.
• Communicate complex technical and architectural concepts to business and senior stakeholders in a clear, simplified manner
• Review and approve test strategies, functional test cases, and data validation approaches.
• Translate business and compliance requirements into NLPenabled analytical use cases, such as: Text classification and categorization, Entity extraction, Risk indicator identification, Summarization of alerts, cases, or documents
• Translate business, regulatory, and analytics requirements into logical data layering and curation strategies that support reporting, analytics, and AI/NLP use cases

Requirements:

• Experience in analyzing business and regulatory requirements and translate them into scalable solution designs.
• Ability to review and approve test strategies, functional test cases, and data validation approaches.
• Ability to design data architectures supporting NLP and AIdriven analytics, including ingestion, curation, and governance of unstructured data within Data Lake, Data warehouse platforms. 
• Strong understanding of data architecture principles and data modelling techniques for designing scalable and efficient data solutions.
• Experience in supporting AI and NLP use cases through data preparation, integration, and optimisation of data pipelines.
• Proficiency in testing, data validation, and quality assurance processes to ensure data accuracy, consistency, and reliability.
• Excellent stakeholder management and communication skills, with the ability to gather requirements and translate business needs into technical solutions.