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Data Engineer-Data Platforms-SnowFlake

IBM2,312 open roles

Where
Bangalore, IN
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Your applicationOpen nowData Engineer-Data Platforms-SnowFlakeIBM · Bangalore, IN
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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. IBM postings stay open a median of 6 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.6%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.0%30 days
This job: posted today

IBM median: 6 days open

The posting

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

As a Data Engineer specializing in Data Platforms-SnowFlake, you play a critical role in building and enhancing Snowflake platforms for client's Data and AI usecases. This position focuses on implementing Data and AI solutions on Snowflake platforms.

Your primary responsibilities will include:

• Design and Implement Solutions: Implement Data and AI usecases on Snowflake platforms, ensuring seamless integration and optimal performance.

• Enhance Platform Capabilities: Build and enhance Snowflake platform capabilities to meet client needs and advance Data and AI applications.

• Leverage Key Skills: Apply expertise in Snowflake, Data Engineering, and Cloud technologies to deliver high-quality solutions.

• Snowflake Platform Expertise: Experience with designing and implementing data and AI usecases on Snowflake platforms, ensuring seamless integration and optimal performance.

• Data Engineering Knowledge: Experience with data engineering principles and practices, including data modeling, data warehousing, and data governance.

• Cloud Technology Proficiency: Experience with cloud technologies, including migration, deployment, and management of cloud-based data platforms.

• Solution Implementation Skills: Experience with implementing data and AI solutions on Snowflake platforms, leveraging expertise in Snowflake, Data Engineering, and Cloud technologies.

• Platform Enhancement Capabilities: Experience with building and enhancing Snowflake platform capabilities to meet client needs and advance Data and AI applications.

• Advanced Snowflake Platform Knowledge: Experience with advanced Snowflake features, including data sharing, data pipelines, and data security. Ability to design and implement complex data and AI usecases on Snowflake platforms.

• Cloud Architecture Expertise: Experience with designing and implementing scalable and secure cloud architectures for data and AI applications. Knowledge of cloud migration, deployment, and management best practices.

• Data Engineering Best Practices: Experience with implementing data engineering best practices, including data modeling, data warehousing, and data governance. Ability to optimize data and AI solutions for performance and scalability.

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