Data Specialist

caterpillar | Experience: 5+ Years | Bangalore | Posted 5 hours ago

Job Description

Packaging AI Solutions and Continuous Improvement

  • Serve as the technical expert and lead on implementing changes for Aftermarket Parts Packaging artificial intelligence and digital tools.
  • Work directly with packaging engineers, IT partners, data owners, and application owners to translate packaging requirements into practical technical solutions.
  • Contribute to solution design, data preparation, integration, testing, user acceptance, deployment, and production support.
  • Maintain, configure, update, and continuously improve deployed artificial intelligence solutions.
  • Implement approved changes to business rules, prompts, workflows, user interfaces, data mappings, reports, and integrations through agile delivery.
  • Monitor performance, user feedback, recurring issues, data quality, and override patterns to identify improvements.
  • Maintain documentation, test evidence, version history, and release records.

 

Application and Solution Development

  • Design, develop, test, deploy, and support full-stack web applications and cloud-based solutions.
  • Build application programming interfaces and backend services that use Snowflake and other enterprise data platforms.
  • Develop applications, utilities, agents, workflows, and decision-support tools for Aftermarket Parts Packaging.
  • Perform enhancements to existing packaging applications, including the Salesforce-based internal packaging application EPSA.
  • Use secure development, automated testing, code review, version control, logging, monitoring, and release-management practices.

 

AI, Data, and Enterprise Integration

  • Create artificial intelligence-enabled applications, agents, search experiences, and engineering workflows using enterprise technologies.
  • Translate packaging standards, calculations, business rules, processes, and expert knowledge into tested decision logic and maintainable digital solutions.
  • Develop data pipelines, analytics, application programming interfaces, and integrations connecting Snowflake, packaging applications, Salesforce-based solutions, and other platforms.
  • Include appropriate human review, exception handling, auditability, and rollback for higher-risk decisions and integrations.
  • Follow enterprise requirements for architecture, cybersecurity, data governance, access management, change management, and production releases.

 

What You Have

Application Development

  • React.js, TypeScript, Hypertext Markup Language, and Cascading Style Sheets
  • Python, including FastAPI or a similar framework
  • Web-based application programming interfaces and full-stack application architecture
  • Application security, automated testing, logging, monitoring, and production support

 

Cloud and DevOps

  • Microsoft Azure
  • Azure Functions, App Services, or similar services
  • Git, code review, continuous integration and deployment pipelines
  • Docker, release management, and rollback

 

Data and AI

  • Strong structured query language and cloud data-platform experience
  • Data modeling, transformation, quality validation, and integration
  • Large language model applications, retrieval-based artificial intelligence, prompts, agents, and search
  • Ability to combine business rules, enterprise data, artificial intelligence output, and human review

 

Enterprise Integration

  • Application programming interface-based system integration and workflow automation
  • Experience enhancing and supporting enterprise applications
  • Experience working within formal security, change, release, and support processes

 

Preferred Qualifications

  • Hands-on experience with Snowflake structured query language, Snowpark Python, or Snowflake Cortex.
  • Experience with Azure OpenAI, LangChain, or LangGraph.
  • Experience with Salesforce configuration or development, including Apex, Lightning Web Components, or Salesforce application programming interfaces.
  • Experience with Microsoft Power Platform or Power BI.
  • Experience supporting and continuously improving enterprise artificial intelligence solutions after launch.
    • Knowledge of packaging, supply chain, manufacturing, aftermarket, or engineering processes.

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