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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Own the data ops CI/CD service and its deployment templates.
Onboard new projects and repositories onto the CD automation; own the standard folder structure template and enforce its use. Maintain build and deployment reliability: pipeline runtime, failure rate, and diagnosability of failed builds.
Drive continuous improvement of the pipeline: build caching, container image hygiene, secret handling, environment promotion, and rollback paths.
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Establish appropriate technical standards, operating practices and governance across the division.
Identify technology risks, capability gaps and technical debt, and drive appropriate remediation andinvestment priorities.
Own and manage enterprise infrastructure across HQ, logistics and warehouse environments, including network and connectivity, servers, virtualisation, storage, cloud infrastructure and data centreservices.
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Maintaining master mapping (Product, Customer, Sales Representative) for IMS Dashboard. Ensuring data is matching versus distributor portal
Managing Veeva CRM to support MCCP upload, data maintenance and troubleshooting if required. Aim to have highest data accuracy, well crafted SOP and data completeness. At one point to be able to provide training for end users
Assist SFE Manager in Profiling, Segmentation and Targeting which includes working with multifunctional team to assess potential through survey and to match sales through ZP Ship to code
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