Data Engineer

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. . 3-5 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.