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Analytics, Senior Data Engineer (Cloud Platforms) 195 views

CVS Health is seeking a Senior Data Engineering – Analytics to further enhance Enterprise Analytics support of the Loyalty and Personalization organization. The Senior Data Engineering will be a hands-on role which will lead the agile team responsible for bringing CVS Health’s front store Personalization efforts to life. The ideal candidate should be a dynamic manager who is capable of being hands-on with the data and has ideally stood up a Personalization Engine (PE) in the past. Candidate should possess a solid foundation in cloud architecture, and are ready to review and enhance the CICD framework. You will lead a cross-functional team in technical expertise as well as work cross-functionally in support of the business, analytics and IT organization.

This position is based out of their Woonsocket, RI office and will report to the Director, Loyalty Execution & Performance Diagnostics within the Enterprise Analytics organization.

  • Will lead an agile and cross-functional team in developing operational business capabilities for the Personalization initiative.
  • Manage the development and release of new machine learning applications/pipelines developed by CVS data scientists into a production environment
  • Maintain and monitor existing machine learning applications and pipelines
  • Design and direct discreet workstreams for junior engineers and developers
  • Work with stakeholders to ensure the implementation of key business capabilities in the personalization engine.
  • Take hands-on role, owning and enabling the integration and refinement of processes and tools with existing CICD framework/processes for PE environment.
  • Define standard operations and processes for Data Scientist workflow, including standards for interacting with the Personalization Engine environment, naming conventions for Data Science pipeline (workbooks, folders, other files, etc)
  • Development of playbooks for data engineering for re-use and scale.
  • Own the PE business process and output, ensuring integration within the existing CVS data ecosystem.
  • Clearly explain to technical and non-technical people the intricacies of the PE architecture, functionality, and capabilities.
  • Responsible for providing a line of sight to system functionality and gaps where capabilities need to be expanded.

#EAAnalytics

Required Qualifications

  • 5+ years managing enterprise engineering personnel and initiatives
  • MCSA – Cloud Platform
  • Demonstrate successfully planning and implementation of highly visible corporate infrastructure initiatives, and providing regular updates to upper management.
  • 3+ years of partnering across multiple groups in a matrix organization (e.g., Data Sciences, IT, Marketing, etc…) to define and implement an automated Personalization Engine.
  • 10+ years proven business experience and technical expertise in data infrastructure roles, with at least 3+ years supporting cloud infrastructure.
  • 3+ years supporting Data Science initiatives working with Semi-structured data, SQL, RDBMS, Hadoop and environments on the cloud (e.g., Azure or AWS) as a technical lead.
  • 3+ years implementing a data science orchestration layer.
  • 3+ years of experience working with machine learning algorithms, building data science platforms leveraging Apache Spark
  • 3+ years of experience optimizing data science algorithms for deployment into a production / operational environment to optimize costs and resource usage
  • 3+ years of experience deploying machine learning and data science pipelines into production using model management solutions and leveraging CICD solutions (e.g., Jenkins) for automation
  • 3+ years of experience configuring cloud platforms and configuring elastic compute environments in a cloud platform
  • Familiarity with and understanding of modern machine learning approaches, algorithms, libraries, and processes for feature selection/engineering
  • Experience building containerized applications and deploying those applications using solutions like Kubernetes
  • Experience with Azure Databricks

Preferred Qualifications

  • 5+ years of experience with implementing a fully productionalized Data Science solution in Azure.
  • MCSE – Cloud Platform and Infrastructure / MCSD – Azure Solutions Architect
  • 1+ years of experience implementing Databricks
  • Databricks – Apache Spark Certified Developer
  • 3+ years of programming experience in Spark/R /Scala and Python
  • Deep understanding of Machine Learning and Artificial Intelligence infrastructure and accompanying best practices.
  • 5+ years of experience implementing and supporting CRM, ESP, marketing cloud, or other personalization technology experience (e.g., Teradata, IBM Unica, Adobe, Dunnhumby, Oracle, Datalogix)
  • Excellent communication and presentation skills with the ability to present complex information in a concise and compelling manner
  • Experience with loyalty programs and Retail

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