Data Engineer-Data Platforms-Databricks

Role overview

Data Engineer-Data Platforms-Databricks at IBM

Responsibilities

• You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results.
• Implement Data and AI use cases: Implement data and AI use cases on the Databricks platform, ensuring seamless integration and optimal performance.
• Support Client Use Cases: Collaborate with clients to understand their data and AI requirements, providing technical expertise to implement use cases on the Databricks platform.

Employment details

• India Data & Analytics Hybrid Professional Bangalore, IN (0063) IBM India Private Limited
• Location: Bangalore [India]

About the employer

• A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide.
• 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.

Additional role details

• You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys.
• At IBM Consulting, curiosity fuels success.
• 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-Databricks, you will play a critical role in building and enhancing the Databricks platform for client's Data and AI use cases.
• This role involves implementing Data and AI use cases on the Databricks platform, requiring strong technical expertise and collaboration.
• Your primary responsibilities will include:
• Enhance Databricks Platform: Build and enhance the Databricks platform to meet client needs, leveraging expertise in data engineering and cloud technologies.
• Databricks Platform Expertise: Experience with building and enhancing Databricks platforms for data and AI use cases, including implementing data and AI solutions.
• Data Engineering Skills: Experience with data engineering principles and practices, including data processing, storage, and retrieval on cloud-based platforms.
• Cloud Technology Knowledge: Experience with cloud technologies, including migration, deployment, and management of data and AI applications on cloud-based infrastructure.
• Implementation Expertise: Experience with implementing data and AI use cases on Databricks platforms, ensuring seamless integration and optimal performance.
• Technical Collaboration: Experience working collaboratively with clients to understand their data and AI requirements, providing technical expertise to implement use cases on the Databricks platform.
• Cloud Migration Knowledge: Exposure to migrating data and AI applications to cloud-based infrastructure, including deployment and management on Databricks platforms.
• Advanced Data Engineering: Exposure to advanced data engineering principles and practices, including data processing, storage, and retrieval on cloud-based platforms.
• AI Solution Implementation: Exposure to implementing AI solutions on Databricks platforms, ensuring seamless integration and optimal performance.