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Senior Performance Analytics (Data Analytics & Platforms)

Senior Performance Analytics (Data Analytics & Platforms)

  • Location Malaysia - Central - Kuala Lumpur
  • Travel required No
  • Job category IT&S Group
  • Relocation available No
  • Job type Professionals
  • Job code 135726BR
  • Experience level Senior
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Job summary

Data & Analytics Platforms (D&AP) Operations Management is an overarching portfolio services which will provide guidance and structure to the rest of D&AP operational delivery. Our presence means the Leadership Team can be assured that operations across D&AP are delivered with consistent approach and standards, good practice is shared between the portfolios and services, a community is built around operational excellence and centralized analytics & insights for better commercial and operational decision making. Our guidance and advice help to minimize risk and maximize service quality.

KEY ACCOUNTABILITIES

  • Design, develop and maintain analytics and insights as per the data & analytics for Data & Analytics Platforms (D&AP) framework
  • Own and build end-to-end consolidated and consistent view of D&AP Analytics & Insights, to provide insight on operations and platform telemetry for performance and utilization analytics
  • Lead the D&AP Analytics and Insights Team to provide industry best practices metrics to define what good looks like for D&AP, including a definition of what data we ought to be capturing, what operation metrics and platform performance indicators we should be measuring against with and techniques we should be considering for achieving business outcomes
  • Define target solution and information architecture that will address existing and recommended data and analytics requirements from across D&AP, and to scale for future requirements and circumstances
  • Develop roadmap, plan, and operating model that will allow D&AP to build out the necessary analytics and insights to address the defined scope and target solution
  • Collaboration with D&AP platform teams and DSoW Enterprise Node team to utilize existing data products and sources for our performance metrics, continuously seek for automation opportunity on our data pipelines, avoid bespoke development while contributing to the enhancement and creation of these metrics’ assets
QUALIFICATIONS
  • Deep and hands-on experience (typically 5 years) in designing, planning, prototyping, productionizing, deploying, maintaining, and documenting reliable and scalable analytics and insights solutions in complex environments that have yielded business impact
  • Strong verbal communication skills and experienced storyteller, proven success in deriving actionable insights from data and quantifying business impact across all levels of bp, including Leadership Team
  • Excellent data analysis and interrogation skills, including advanced level use of data visualization and science tools such as Power BI and Dataiku
  • Development experience in one or more object-oriented programming languages (e.g. Python and R); advanced SQL knowledge.
  • Recent experience utilizing data analytics and modeling in Azure and AWS services such as Azure ML and AWS Sagemaker
  • Experience designing and implementing large-scale distributed systems

DESIRABLE CRITERIA
  • Autonomy in problem identification and problem breakdown: end-to-end project ownership: independently identify problems to be solved in your team / sub-area based on in-depth technical and business understanding and able to break them down into actionable sub-problems and tasks
  • Data Manipulation: familiar with the data sources needed to carry out analysis in your team's scope; you can build simple data pipelines (if needed);
  • Automation: integrate existing tools to automate data manipulation, analysis and quality control and collaborate with data engineers to identify new tools or approaches to analysis where needed
  • Coding: contribute to internal and/or external libraries through raising issues, adding documentation and/or contributing new features; write clean, re-usable code in a language that runs in production at bp
  • Right approach / tool choice: deep understanding of a wide range of commonly available Performance Analytics approaches and tools and choose the right ones to solve the problem
  • Scalability, Reliability, Maintenance: proven experience in building scalable and re-usable systems and automating operations
  • Data Domain Knowledge: proven understanding of data sources and data and analytics requirements and typical SLAs associated to data provisioning and consumption at enterprise scale, with experience in analysis of data or other enterprise platform operations activities

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