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Data & Analytics Engineer - Consultant

KPMG Global Services · Pune, Maharashtra, India

Mixed hiring record · median 42 days open

100100

Hiring signal

Actively hiring

Posted today · still listed on the employer's own board · How we score

All reasons
  • 34% of this employer's openings are over 60 days old

In its favour

  • Posted today
  • Still listed on the employer's own board

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Data & Analytics Engineer - Consultant at KPMG Global Services. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

Snowflake Cortex AI Engineer: Consultant

  • 4+ years Snowflake experience with strong grasp of architecture (compute–storage separation, micro-partitions, virtual warehouses, RBAC) and features (Snow pipe, Streams/Tasks, Dynamic Tables).
  • Design, develop, and deploy Conversational AI solutions on Snowflake using Cortex Analyst, Cortex Agents, Cortex Search, and Snowpark, enabling natural language interaction with enterprise data.
  • Build and maintain Streamlit applications on Snowflake to deliver secure, scalable, and user-friendly AI-powered analytics and chatbot experiences.
  • Develop robust ETL/ELT data pipelines using Snowflake, Python, SQL, and orchestration tools to ingest, transform, and curate data across Bronze, Silver , and Gold layers.
  • Create and manage semantic models, business metrics, governed data products, and AI-ready data models to improve the accuracy and reliability of AI-generated insights.
  • Implement best practices for performance optimization, security, RBAC, data governance, monitoring, CI/CD, Git integration, and automated deployments within Snowflake environments.
  • Collaborate with business stakeholders, data engineers, and analytics teams to translate business requirements into scalable AI, analytics, and data engineering solutions, while troubleshooting and optimizing production workloads.

Snowflake Cortex AI Engineer: Consultant

  • 4+ years Snowflake experience with strong grasp of architecture (compute–storage separation, micro-partitions, virtual warehouses, RBAC) and features (Snow pipe, Streams/Tasks, Dynamic Tables).
  • Design, develop, and deploy Conversational AI solutions on Snowflake using Cortex Analyst, Cortex Agents, Cortex Search, and Snowpark, enabling natural language interaction with enterprise data.
  • Build and maintain Streamlit applications on Snowflake to deliver secure, scalable, and user-friendly AI-powered analytics and chatbot experiences.
  • Develop robust ETL/ELT data pipelines using Snowflake, Python, SQL, and orchestration tools to ingest, transform, and curate data across Bronze, Silver , and Gold layers.
  • Create and manage semantic models, business metrics, governed data products, and AI-ready data models to improve the accuracy and reliability of AI-generated insights.
  • Implement best practices for performance optimization, security, RBAC, data governance, monitoring, CI/CD, Git integration, and automated deployments within Snowflake environments.
  • Collaborate with business stakeholders, data engineers, and analytics teams to translate business requirements into scalable AI, analytics, and data engineering solutions, while troubleshooting and optimizing production workloads.

Snowflake Cortex AI Engineer: Consultant

  • 4+ years Snowflake experience with strong grasp of architecture (compute–storage separation, micro-partitions, virtual warehouses, RBAC) and features (Snow pipe, Streams/Tasks, Dynamic Tables).
  • Design, develop, and deploy Conversational AI solutions on Snowflake using Cortex Analyst, Cortex Agents, Cortex Search, and Snowpark, enabling natural language interaction with enterprise data.
  • Build and maintain Streamlit applications on Snowflake to deliver secure, scalable, and user-friendly AI-powered analytics and chatbot experiences.
  • Develop robust ETL/ELT data pipelines using Snowflake, Python, SQL, and orchestration tools to ingest, transform, and curate data across Bronze, Silver , and Gold layers.
  • Create and manage semantic models, business metrics, governed data products, and AI-ready data models to improve the accuracy and reliability of AI-generated insights.
  • Implement best practices for performance optimization, security, RBAC, data governance, monitoring, CI/CD, Git integration, and automated deployments within Snowflake environments.
  • Collaborate with business stakeholders, data engineers, and analytics teams to translate business requirements into scalable AI, analytics, and data engineering solutions, while troubleshooting and optimizing production workloads.

Skills

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