AI-Driven Data Products Designer for Enterprise Platforms

International Business Machines Corporation; Houston (TX); Remote; USD 120,000 - 180,000; Full time

Job summary

IBM Consulting is seeking a Data Products Designer to shape business-aligned data products within a large data re-engineering program. You will define data product structures, contracts, metadata, and ensure downstream analytics, ML and GenAI use cases can consume them on Databricks and AWS.

You will collaborate with business and technical stakeholders to establish scope, ownership, SLAs, data quality rules, and governance while re-engineering legacy structures into scalable, well-modeled data

Qualifications

• Advanced data modelling/design/architecture for complex enterprise environments.
• Strong SQL skills; experience with Databricks, Delta Lake, Unity Catalog, AWS data services.
• Experience mapping source-to-target, data contracts, SLAs, and governance with data engineers.

Responsibilities

• Define data products: scope, ownership, consumers, SLAs, data contracts.
• Design logical/physical data models for data products on Databricks and AWS.
• Re-engineer legacy data structures into reusable data products.
• Define data quality rules, lineage, and governance with engineers and governance teams.
• Produce design documentation and review designs with stakeholders.
• Develop data solutions on Big Data and lakehouse tech; provide technical leadership.

Skills

Data modelling

Data architecture

SQL

Databricks

AWS data services

Data governance

Tools

Databricks (Delta Lake)

Erwin / ER Studio

Fivetran

Collibra

Job description

IBM Consulting is seeking a Data Products Designer to shape business-aligned data products within a large data re-engineering program. You will define data product structures, contracts, metadata, and ensure downstream analytics, ML and GenAI use cases can consume them on Databricks and AWS.

You will collaborate with business and technical stakeholders to establish scope, ownership, SLAs, data quality rules, and governance while re-engineering legacy structures into scalable, well-modeled data