Data Engineer-Data Platforms-SnowFlake

Introduction

A career in IBM Consulting is grounded in long-term client relationships and collaboration with teams across the globe. You’ll partner with leading organizations across industries to help define their hybrid cloud and AI strategies. With guidance from strategic partners, IBM technology, and Red Hat, you’ll have the capabilities to drive meaningful change and help accelerate client outcomes. At IBM Consulting, curiosity powers success—you’ll be encouraged to question the status quo, experiment with new ideas, and develop solutions that deliver tangible results. Our growth- and empathy-focused culture supports your long-term career development while recognizing the value of your individual skills and experiences.

Your Role And Responsibilities

As a Data Engineer specializing in Data Platforms-SnowFlake, you will take a key role in creating and improving Snowflake platforms that support clients’ Data and AI usecases. This position focuses on implementing Data and AI usecases on Snowflake platforms, leveraging strong technical expertise and close collaboration.

Your Primary Responsibilities Will Include

• Implement Data and AI usecases: Implement Data and AI usecases on Snowflake platforms to ensure smooth integration and strong performance.
• Enhance Snowflake platform: Build and improve Snowflake platforms to align with clients’ Data and AI requirements, applying data engineering principles and best practices.
• Leverage Cloud capabilities: Use Cloud capabilities to enable Snowflake platform development while ensuring scalability and reliability.
  
  

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• Exposure to Snowflake platforms: Familiarity with Snowflake architecture, capabilities, and best practices for implementing Data and AI usecases.
• Experience with Data Engineering: Understanding of data engineering fundamentals, including data modeling, data warehousing, and ETL processes.
• Cloud computing skills: Knowledge of Cloud capabilities—such as scalability, reliability, and security—to support Snowflake platform development.
• Data and AI usecase implementation: Experience implementing Data and AI usecases on cloud-based platforms, ensuring seamless integration and optimal performance.
• Data platform development: Exposure to developing and enhancing data platforms to meet business needs, using data engineering principles and best practices.
  
  

Preferred Technical And Professional Experience

• Cloud Security Knowledge: Exposure to Cloud security features, including data encryption, access controls, and compliance, to support secure Snowflake platform development.
• Advanced Data Modeling: Experience using advanced data modeling approaches, including data warehousing and ETL processes, to enable complex Data and AI usecases.
• Scalability Optimization: Understanding of scalability optimization methods, including data partitioning and caching, to maintain high-performance Snowflake platform operation.