Senior Data Architect — Hybrid Data Products & BI

Kraft Heinz; Toronto; Hybrid; CAD 96,000 - 120,000; Full time

Benefits offered by this job

Bonus eligibility

Job summary

Kraft Heinz in Toronto is seeking a Senior Data Architect to lead domain data architecture and develop scalable data products. You will collaborate with data scientists, engineers, and business stakeholders to deliver robust data models and semantic layers that support BI and AI use cases.

The role emphasizes data warehouse expertise, cloud services experience, and coding with tools like ERWin/ER/Studio, dbt, and Python. Hybrid work arrangement applies, with three on-site days weekly.

Qualifications

• Bachelor’s degree in computer science, data science, engineering, or related field.
• Certifications in Data Management, Data Modelling and Cloud services is preferred.
• At least 5 years of experience designing scalable data models.
• Strong background in data warehouse implementation.
• Experience with data modeling tools (ERWIN, ER/STUDIO).
• Translate business requirements into technical data solutions.

Responsibilities

• Collaborate with product owners and data consumers to define data product needs.
• Design data models for source and master data products with schema and definitions.
• Build semantic models to support BI, AI, and analytics use cases.
• Review data model development and provide deployment approvals.
• Document architecture artifacts and participate in governance forums.
• Support data and BI engineering during build phases.

Skills

Data modeling

Data warehouse

ETL/ELT

Python/dbt

Cloud services

Agile/Jira

Cross-functional collab

Education

Bachelor's degree in CS/Eng/Data Science

Data management certs (preferred)

Tools

ERWin

ER/Studio

dbt

Pandas

Job description

Kraft Heinz in Toronto is seeking a Senior Data Architect to lead domain data architecture and develop scalable data products. You will collaborate with data scientists, engineers, and business stakeholders to deliver robust data models and semantic layers that support BI and AI use cases.

The role emphasizes data warehouse expertise, cloud services experience, and coding with tools like ERWin/ER/Studio, dbt, and Python. Hybrid work arrangement applies, with three on-site days weekly.