Data Products Designer, Lakehouse & AI Architect

IBM; Austin (TX); Remote; USD 120,000 - 160,000; Full time

Job summary

IBM Consulting is seeking a Data Products Designer to 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.

Work with stakeholders to design scalable data models on Databricks and AWS, re-engineer legacy structures, and maintain documentation and data quality standards. This role offers leadership across a data-centric team.

Qualifications

• Advanced expertise in data modelling, data design, or data architecture.
• Strong capability in dimensional, relational, and lakehouse modelling.
• Excellent SQL skills with Databricks and AWS data services.
• Experience designing scalable data solutions for real-time data and APIs.
• Ability to define data quality, lineage, and governance with engineers.

Responsibilities

• Define data products: scope, ownership, consumers, SLAs, and data contracts.
• Design logical/physical data models for data products on Databricks and AWS.
• Re-engineer legacy data structures into reusable data products.
• Define source-to-target mappings for pipelines via Fivetran and SAP sources.
• Align SAP-native data products with non-SAP data models.
• Maintain models and artifacts in enterprise data modeling tools.
• Produce design documentation and review designs with engineers and product owners.
• Design and develop data solutions on Big Data and lakehouse tech with API access.
• Provide technical leadership on complex data solutions and best practices.

Skills

Data modelling

Data design

Data architecture

SQL skills

Databricks

AWS services

Tools

Erwin

ER Studio

Fivetran

Collibra

Job description

IBM Consulting is seeking a Data Products Designer to 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.

Work with stakeholders to design scalable data models on Databricks and AWS, re-engineer legacy structures, and maintain documentation and data quality standards. This role offers leadership across a data-centric team.