Partner with business product owners, technology teams, and senior stakeholders to provide trusted technical advice, influence strategic decisions, and foster adoption of data science solutions across the organisation.
Contribute to the growth of the Data Science community by sharing knowledge, mentoring team members, promoting best practices, and bringing insights from internal and external projects to continuously improve capabilities and business outcomes.
Design, build, and enhance data science and AI products that contribute to a Unified Revenue Growth Management (RGM) Engine, enabling the evolution from centralized insights to AI-powered decision-making and execution.
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Conduct Data Discovery, Data Assessment and Data Workshops with customers to understand current architecture, data sources, data quality and business requirements.
Analyze customer data environments and recommend approaches for data consolidation, integration, migration, modernization and analytics.
Support presales activities, including discovery sessions, solution discussions, technical proposals, effort estimation, POCs and customer presentations.
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Salary: Competitive, based on experience + Performance BonusesWork Hours: 8.30am to 5.00pmEmployment Type: Full-Time / Part-Time / Contract
Why Join Us?
Supportive & Friendly Work EnvironmentCareer Growth Opportunities in AccountingWork-Life Balance & Fixed Working HoursOn-the-Job Training ProvidedPerformance Incentives
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Strong understanding of B2B business environment, needs and conditions and proven knowledge of digital marketing
Secure knowledge on visualization platforms that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics via dashboards. (e.g. Power BI preferred, Tableau, SAC)
Proven experience in assembling large, complex data sets that meet functional / non-functional business requirements.
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Operate DataPipes (EKS + Airflow) for ingestion orchestration, ensuring high availability and version-controlled configurations via IaC (CloudFormation/CDK).
Maintain & enhance logging, monitoring, observability & DevOps automation via modern tools such as CloudWatch, Splunk, PagerDuty, Slack, ServiceNow, Snowflake observability features.
Maintain and manage the observability of infrastructure environment of Data Engineering, including monitoring, logging, alerting, notification and so on, focusing on the monitor system performance and proactively identify and resolve issues. Optimize system performance and resource utilization.
Work closely with cross-functional teams to understand business needs and deliver data-driven insights.
Provide technical support, data ops environment on-call and training to team members and stakeholders on data operation tools and best practices.
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Build and optimize ETL/ELT frameworks supporting batch and near real-time processing.
Develop enterprise Data Warehouse and Lakehouse solutions for analytics, reporting, and AI/ML use cases.
Create and maintain dimensional data models including Fact and Dimension tables, Star Schema, Snowflake Schema, and Slowly Changing Dimensions (SCD).
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