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 Data Products Designer to design and shape business-aligned data products as part of a large data re-engineering program. You will define data product structure, models, contracts and metadata that downstream analytics, ML and GenAI use cases will consume.

Responsibilities

Work with business and technical stakeholders to define data products: scope, ownership, consumers, SLAs, and data contracts. Design logical and physical data models (conceptual, dimensional, and lakehouse/medallion layers) for data products on Databricks and AWS. Re-engineer legacy data structures and transformation logic into well-modeled, reusable data products rather than replicating them as-is. Define source-to-target mappings for pipelines ingested via Fivetran and from SAP and non-SAP sources. Assess and align with SAP-native data products so that SAP and non-SAP data are modeled consistently. Maintain models and design artifacts in the enterprise data modeling tools Define data quality rules, business definitions, and lineage expectations with data engineers and governance teams. Produce design documentation and review designs with Data Engineers, Architects, and Product Owners. Design and develop data solutions on Big Data and lakehouse technologies, including API-based data access, writing and debugging complex code where needed. Provide technical leadership on the design of complex, high-quality and efficient data solutions, guiding team members on standards and approach. Optimize the performance, scalability, and reliability of data products and the underlying data platform. Collaborate with delivery teams to deliver solutions that meet business requirements and stakeholder expectations. This job can be performed from anywhere in the US Preferred Education None Required Technical And Professional Expertise Must be able to travel 4 days per week (mandatory). Advanced expertise in data modelling, data design, or data architecture, with demonstrated ability to design scalable data models and architectures for complex enterprise environments. Strong hands-on expertise in dimensional, relational, and lakehouse data modelling, including data products/data mesh concepts and source-to-target mapping. Strong SQL skills and experience with Databricks (Delta Lake, Unity Catalog), AWS data services, and data modelling tools such as Erwin or ER Studio. Experience designing scalable, reliable data solutions for unstructured and real-time/near-real-time data using Kafka, Amazon EventBridge, Amazon SQS, or similar technologies. Ability to optimize modern data platforms for performance and translate business requirements into reusable, governed data products. Preferred Technical And Professional Experience Experience with Fivetran or similar ELT tools, Collibra or similar metadata/catalogue platforms, and relational-to-Databricks/Lakebase migrations. Knowledge of SAP IS-U, SAP-native data products, SAP Business Data Cloud, and SAP BTP. Experience in the utilities or energy industry. Databricks and/or AWS certification, with Agile delivery experience. Exposure to NLP, analytics, statistical, or big-data technologies.