Management Consultant - Data Engineer

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-Databricks, you will play a critical role in building and enhancing the Databricks platform for client's Data and AI use cases. This position is responsible for implementing Data and AI use cases on the Databricks platform. Your primary responsibilities will include: • Implement Data and AI Use Cases: Design, develop, and deploy data and AI solutions on the Databricks platform to meet client needs, driving business value through data-driven insights. • Enhance Databricks Platform: Collaborate with stakeholders to identify areas for improvement and implement enhancements to the Databricks platform, ensuring optimal performance and scalability. • Drive Solution Delivery: Lead the delivery of data and AI solutions, working closely with clients to understand their requirements and ensure successful project outcomes. *This job can be performed from anywhere in the US. • Deep Expertise in Databricks: Proven experience with designing, developing, and deploying data and AI solutions on the Databricks platform, with a strong understanding of its architecture and capabilities. • Experience with Data Engineering: Skilled in data engineering principles, including data processing, storage, and retrieval, with the ability to apply this knowledge to build scalable and efficient data pipelines. • Cloud Computing Knowledge: Experience with cloud-based technologies and infrastructure, including migration, deployment, and management of cloud-based data platforms. • Certification in Data and AI: Possession of relevant certifications in data engineering, data science, or AI, demonstrating expertise in implementing data and AI use cases on cloud-based platforms. • Experience with Solution Delivery: Proven track record of leading the delivery of data and AI solutions, working closely with clients to understand their requirements and ensure successful project outcomes. • Cloud Migration Expertise: Experience with migrating data platforms to cloud-based infrastructure, including planning, execution, and post-migration optimization. Ability to assess existing infrastructure and develop strategies for seamless migration to cloud-based environments. • Advanced Data Engineering: Deep understanding of data engineering principles, including data warehousing, ETL, and data governance. Ability to design and implement scalable and efficient data pipelines, leveraging expertise in data processing, storage, and retrieval. • AI Solution Development: Experience with developing and deploying AI solutions on cloud-based platforms, including natural language processing, machine learning, and deep learning. Ability to collaborate with stakeholders to identify business opportunities and develop AI-powered solutions to drive business value. United States Data & Analytics Hybrid Professional Multiple Cities Kansas City Rocket Center JEFFERSON CITY Naples TUCSON Newark RESEARCH TRIANGLE PARK Armonk Yorktown Heights DURHAM Denver Capitola Irving Essex Junction Tulsa Charlotte Norwalk Boston Bellevue BOISE Miami Atlanta LOS ANGELES Columbus Santa Monica JERSEY CITY Philadelphia San Jose Santa Clara Denver Minneapolis Dallas SOMERVILLE Houston Austin San Francisco Seattle (0147) International Business Machines Corporation Architecture Artificial Intelligence Cloud Computing Data Governance Data Processing Data Science Data Warehousing Deep Learning Design Extract, Transform, Load Infrastructure Machine Learning Management Natural Language Processing Optimization Pipelines Planning Storage Cloud Migration Data Engineering Databricks Use Cases Solution Delivery