Data Architect

About the Role

The Data Architect owns the data modeling and platform design blueprint for a defined domain, reporting into the Chapter Lead: Data Architecture. The role designs data models, defines data platform structure (e.g., data lake/warehouse organization), and sets standards that Data Engineers build against distinct from a senior Data Engineer, this role owns the modeling and governance layer, not the day-to-day pipeline code.

Key Responsibilities

• Design data models (dimensional, Data Vault, or equivalent) and define database/data platform architecture for the assigned domain.
• Establish data standards, canonical data structures, and naming/classification conventions for the domain.
• Define data integration and data governance requirements, partnering with Data Engineering and Data Governance teams.
• Review and approve data pipeline and data product designs built by Data Engineers for adherence to architecture standards.
• Support data quality, metadata, and lineage initiatives, ensuring data is documented and traceable from source to use.
• Advise business and technical stakeholders on data architecture options and trade-offs for their use cases.
• Evaluate and recommend data platform technologies (e.g., Snowflake, Databricks, BigQuery) in partnership with Engineering leadership.

Key Skills & Experience

• 7–9 years in data engineering, data modeling, or data architecture, including demonstrated ownership of data modeling or platform design decisions.
• Strong hands-on experience with data modeling techniques (dimensional modeling, Data Vault 2.0, or similar).
• Practical experience with at least one cloud data platform (Snowflake, Databricks, BigQuery, or Redshift).
• Working knowledge of ETL/ELT design, ensuring architecture supports engineers building pipelines against it.
• Experience establishing data governance practices — data contracts, lineage tracking, and catalog/metadata management.
• Strong communication skills, able to explain modeling and platform trade-offs to both technical and business stakeholders.
• Cloud data certification (e.g., Snowflake SnowPro, Azure/AWS/GCP data certifications) is a plus, not required.
• Bachelor's degree in Computer Science, Information Systems, or related field.