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Cognizant

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Architect

Summary

Designs and delivers large-scale data and ML platforms on Azure Databricks and Azure ML for media workflows, focusing on scalable analytics, audience engagement models, and secure, responsible AI solutions.



Job Summary

Architect role for an experienced professional with twelve to sixteen years of background in designing and delivering large scale data and machine learning platforms using Azure Databricks and Azure Machine Learning in media and entertainment domain focused environments. The role uses a hybrid work model in day shift and emphasizes secure scalable and responsible solutions.


Responsibilities

  • Design robust Azure Databricks based data platforms that support high volume media content workflows and complex analytics needs for global business teams in a hybrid work environment
  • Architect end to end Azure Machine Learning solutions that enable advanced prediction models for audience engagement content performance and personalized recommendations in media and entertainment use cases
  • Define scalable data lake and medallion architecture patterns on Azure that ensure reliable ingestion curation and consumption of structured and unstructured media data assets
  • Coordinate with product owners and domain experts to translate media and entertainment business goals into practical data and machine learning features and implementation roadmaps
  • Guide engineering teams in implementing secure and cost optimized Azure Databricks clusters jobs and notebooks aligned with organizational governance and compliance standards
  • Establish best practices for machine learning lifecycle management including experiment tracking model versioning model retraining and responsible deployment using Azure Machine Learning
  • Collaborate with data engineers data scientists and platform specialists to troubleshoot performance issues and continuously improve data pipelines and model serving pipelines
  • Prepare detailed solution design documents and architecture diagrams that clearly describe integration points data flows and operational responsibilities for all stakeholders
  • Review existing media analytics solutions and recommend modernization approaches that leverage Azure Databricks Delta architecture and managed machine learning capabilities
  • Define monitoring strategies and observability standards for batch and streaming data jobs as well as machine learning endpoints to maintain reliable service levels for business critical workloads
  • Develop governance guidelines for data quality feature stores and model management that uphold ethical use of data and fair outcomes in media and entertainment decision processes
  • Coordinate security controls such as role based access policies encryption configurations and network isolation to protect sensitive content and usage data within the Azure ecosystem
  • Document reusable reference architectures patterns and playbooks that accelerate future Azure Databricks and Azure Machine Learning projects and help teams adopt consistent engineering practices

    • Qualifications

  • Describe educational background such as degree in computer science data engineering or related field combined with substantial industry experience in data and analytics architecture
  • Highlight mandatory experience in Azure Databricks including cluster design job orchestration notebook development and performance tuning for data heavy media workloads
  • Emphasize mandatory expertise in Azure Machine Learning for building training evaluating and deploying machine learning models at scale with strong focus on automation and repeatability
  • Explain proven experience working in media and entertainment domain including exposure to content supply chains digital distribution streaming analytics and audience measurement scenarios
  • Detail strong proficiency in data engineering concepts such as distributed processing data modeling streaming data pipelines and data lakehouse patterns on Azure cloud platforms
  • Mention experience working in hybrid work models and collaborating across distributed teams using modern agile practices documentation standards and transparent communication
  • State nice to have familiarity with additional Azure services such as Azure Data Factory Azure Synapse and Azure Storage that complement Azure Databricks and Azure Machine Learning in enterprise solutions
  • Describe ability to communicate complex technical concepts in clear business oriented language to stakeholders across technology and media business functions

    • Show

    See also

    ArchitectureAzureRemote WorldwideJavaScriptPython