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 products and services fulfilling business reporting needs. • Collaborate closely with product and tech teams to gather business and data requirements for building effective dashboards and reports. • Assist in conducting Data Heros workshops/ trainings to cultivate JP staffs in using analytical and BI tools for business analytics. • Support data governance initiatives in form of driving data stewardship and data lifecycle management. • Participate in cyber security and governance assessments to ensure compliance with data privacy regulations and industry standards. • Generate and implement relevant codes for data transformation (ETL), normalisation and aggregation tasks with relevant Data quality monitoring recommendations. Key Deliverables • Implement automated data pipelines and monitoring tools, meeting the data quality and lifecycle management standards. • Develop and implement appropriate data sources and relevant data transformation techniques to maximise automation and self service capabilities for end users. • Build and design reports/dashboards visualizations effective at telling stories and drawing out actionable insights. • Develop and execute comprehensive deployment strategies and plans for BI tools/ platform adoption, tailored to the different needs and competency levels of business users. Qualifications: • Completed a degree in Business Analytics, Data Science, Data Engineering or a related field. • 5-10 years relevant experience in ETL/ELT & data warehousing using Saas/PaaS such as Snowflake, AWS Redshift and other related open-source tools such dbt • Strong foundation in related SQL languages such as PostgreSQL, Oracle SQL and Python 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 integration tools that are critical for organization's success in 5-years AI roadmap. • Mentorship and guidance from experienced AI & data management professionals.