Data Engineer-Data Platforms-Databricks

Introduction
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.
Your Role And Responsibilities
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 skills and attention to detail.
Your Primary Responsibilities Will Include
Implement Data and AI Use Cases: Implement data and AI use cases on the Databricks platform, ensuring seamless integration and optimal performance. This involves designing, developing, and deploying scalable data pipelines and architectures that meet business requirements.
Enhance Databricks Platform: Continuously enhance and improve the Databricks platform to support evolving client needs and emerging trends in Data and AI. This includes staying up-to-date with new features, best practices, and industry developments related to Databricks and cloud-based data engineering.
Preferred Education
Master's Degree
Required Technical And Professional Expertise
Exposure to Databricks Platform: Experience with implementing data and AI use cases on the Databricks platform, including designing, developing, and deploying scalable data pipelines and architectures.
Data Engineering Skills: Experience working with data engineering principles, practices, and tools, particularly in cloud-based environments.
Cloud Computing Knowledge: Exposure to cloud computing concepts, technologies, and platforms, including those related to data engineering and Databricks.
Implementation Expertise: Experience with implementing data and AI solutions, ensuring seamless integration and optimal performance.
Technical Skills: Proficiency in technical skills relevant to Databricks, data engineering, and cloud computing.
Preferred Technical And Professional Experience
Cloud Computing Knowledge: Exposure to cloud computing concepts, technologies, and platforms, including those related to data engineering and Databricks, is beneficial for this role.
Data Engineering Principles: Familiarity with data engineering principles and practices, particularly in cloud-based environments, is advantageous for implementing data and AI use cases on the Databricks platform.
Technical Proficiency: Proficiency in technical skills relevant to Databricks, data engineering, and cloud computing is desirable for this position.

Work arrangement
Hybrid