Key Responsibilities:• Design and build data pipelines and consolidated data sources for performance,scalability, and real-time processing.• Define clear objectives, metrics and deployment strategies for data productsand services fulfilling business reporting needs.• Collaborate closely with product and tech teams to gather business and datarequirements for building effective dashboards and reports.• Assist in conducting Data Heros workshops/ trainings to cultivate JP staffs inusing analytical and BI tools for business analytics.• Support data governance initiatives in form of driving data stewardship and datalifecycle management.• Participate in cyber security and governance assessments to ensure compliancewith data privacy regulations and industry standards.• Generate and implement relevant codes for data transformation (ETL),normalisation and aggregation tasks with relevant Data quality monitoringrecommendations.Key Deliverables• Implement automated data pipelines and monitoring tools, meeting the dataquality and lifecycle management standards.• Develop and implement appropriate data sources and relevant datatransformation techniques to maximise automation and self service capabilitiesfor end users.• Build and design reports/dashboards visualizations effective at telling storiesand drawing out actionable insights.• Develop and execute comprehensive deployment strategies and plans for BItools/ platform adoption, tailored to the different needs and competency levelsof business users.Qualifications:• Completed a degree in Business Analytics, Data Science, Data Engineering or arelated field.• 3-5 years relevant experience in ETL/ELT & data warehousing using Saas/PaaSsuch as Snowflake, AWS Redshift and other related open-source tools such dbt• Strong foundation in related SQL languages such as PostgreSQL, Oracle SQL andPython for data wrangling and analysis.• Strong knowledge in data visualization tools such as PowerBI/Tableau• Experience with iPaaS solutions i.e. Workato, Boomi, MuleSoft will be a plus.• Relevant certifications in data engineering fundamentals or cloud platforms(e.g., AWS Certified Data Engineer, Azure Data Engineer Associate).• Strong business acumen & analytical mindset for problem-solving, adaptable,eager to learn, and enthusiastic about new technologies.Benefits:• Hands-on experience working with state-of-the-art data platform and integrationtools that are critical for organization's success in 5-years AI roadmap.• Mentorship and guidance from experienced AI & data managementprofessionals.